Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic intervent...Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.展开更多
Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger gra...Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger grain size than unidirectional rolling aged(URA)sheet due to the occurrence of dynamic recovery during rolling which reduces the dislocation density and delays dynamic recrystallization(DRX).The URA sheet has basal texture and RD favored texture while CRA sheet has multiple-peak texture.Both sheets precipitate β'phase and CRA sheet exhibits a stronger aging response.The CRA sheet has higher yield strength and tensile strength than URA sheet,with reduced yield strength anisotropy but increased tensile strength anisotropy.Taking into account different strengthening mechanisms,although the finer grain size of URA sheet enhances grain boundary strengthening,CRA sheet is more responsive to aging,leading to superior aging-precipitated phase strengthening and consequently higher yield strength.展开更多
Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which c...Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios.展开更多
Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central...Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central Asia, exerts a substantial influence on avian migration patterns. Species traversing such ecological barriers may adopt multiple optimal routes, which can contribute to the formation of migratory divides. From 2018 to 2021, the migration routes of 13 adult Common Cuckoos (Cuculus canorus) breeding in the north of the Qinghai-Tibet Plateau were tracked using satellite transmitters. We found Common Cuckoos have two primary migration routes: western and eastern, respectively following western and eastern edges of the Qinghai-Tibet plateau. The eastern and western routes are likely the optimal routes for the Central Asian Common Cuckoos population to navigate the Qinghai-Tibet Plateau. Furthermore, two individuals exhibited intermediate migration routes, suggesting attempted traverses of the Qinghai-Tibet Plateau, although neither completed the migration. These intermediate routes may indicate migratory behavior influenced by hybridization between eastern and western populations or migratory flexibility. Common Cuckoos exhibit significantly faster migration speed, flight speed, and shorter stopover durations during spring compared to autumn. The observed seasonal differences in migration behavior support birds following time-minimization strategies during spring migration. These results revealed the diverse migration routes of Common Cuckoos shaped by the Qinghai-Tibet Plateau and seasonal variation in migration patterns.展开更多
To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and en...To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.展开更多
As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the trans...As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.展开更多
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To sa...Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.展开更多
Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current so...Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.展开更多
This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operat...This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operational characteristics,optimization objectives,vehicle types,and time constraints.Based on literature retrieval results from the Web of Science database,the paper analyzes the current state and trends in VRP research,providing detailed explanations of VRP models and algorithms applied to various scenarios in recent years.Additionally,the article discusses limitations in existing research and provides perspectives on future development trends in VRP research.This review offers researchers in the VRP field a comprehensive overview while identifying future research directions.展开更多
This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocatio...This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.展开更多
This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to...This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to contribute to rural revitalization, including the optimization of professional and curriculum systems, the deepening of industry-education integration and school-enterprise cooperation, the enhancement of brand development and marketing efforts, the strengthening of cross-border e-commerce and international cooperation capabilities, and the improvement of policy support and resource allocation systems. The findings aim to provide a theoretical foundation for Guizhou vocational education to support local economic development.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction a...Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction and expansion projects has gradually become a key measure to improve the service level of the road network and alleviate traffic congestion.Meanwhile,route design is a core aspect of highway reconstruction and expansion projects,and its scientific nature and quality can directly affect the safety,economy,and future operational efficiency of the highway.Therefore,this article provides a detailed analysis of the principles and requirements of route design for highway reconstruction and expansion projects.Additionally,it delves into the design process and key technologies applied in route design for these projects.展开更多
A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm ...A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm and an electro-chemical stability window of 3.8 V.Additionally,an all-solid-state lithium-ion battery using Li_(3)YCl_(3)Br_(3) and LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM811)as the cathode material achieves a capacity retention of 93%after 200 cycles at 0.3C and maintains a specific capacity of 115 mA·h/g during 2C cycling.This exceptional performance is attributed to the high oxidative stability of Li_(3)YCl_(3)Br_(3) and the in-situ formation of Y_(2)O_(3) inert protective layer on the NCM811 surface under high voltage.Consequently,the study demonstrates the feasibility of a simple,cost-effective wet-chemistry route for synthesizing multi-component halides,highlighting its potential for large-scale production of halide solid electrolytes for practical applications.展开更多
Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,com...Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.展开更多
The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the...The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF).展开更多
In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorith...In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing.The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area.Then,the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission.Relay nodes are selected layer by layer,starting from the outermost cluster heads.Finally,the inter-layer routing mechanism is integrated with regional partitioning and clustering methods to develop the WRSN energy optimization algorithm.To further optimize the algorithm’s performance,we conduct parameter optimization experiments on the relay routing selection function,cluster head rotation energy threshold,and inter-layer relay structure selection,ensuring the best configurations for energy efficiency and network lifespan.Based on these optimizations,simulation results demonstrate that the proposed algorithm outperforms traditional forward routing,K-CHRA,and K-CLP algorithms in terms of node mortality rate and energy consumption,extending the number of rounds to 50%node death by 11.9%,19.3%,and 8.3%in a 500-node network,respectively.展开更多
Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are fac...Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).展开更多
Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectu...Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.展开更多
Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation o...Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2023YFD1800403 and 2023YFD1800404)。
文摘Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.
基金Project(2023GK2020)supported by the Key Research and Development Program of Hunan Province,China。
文摘Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger grain size than unidirectional rolling aged(URA)sheet due to the occurrence of dynamic recovery during rolling which reduces the dislocation density and delays dynamic recrystallization(DRX).The URA sheet has basal texture and RD favored texture while CRA sheet has multiple-peak texture.Both sheets precipitate β'phase and CRA sheet exhibits a stronger aging response.The CRA sheet has higher yield strength and tensile strength than URA sheet,with reduced yield strength anisotropy but increased tensile strength anisotropy.Taking into account different strengthening mechanisms,although the finer grain size of URA sheet enhances grain boundary strengthening,CRA sheet is more responsive to aging,leading to superior aging-precipitated phase strengthening and consequently higher yield strength.
基金supported by the National Natural Science Foundation of China(Project No.52172321,52102391)Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)+1 种基金China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios.
基金supported by the National Natural Science Foundation of China(Grant No.31672296).
文摘Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central Asia, exerts a substantial influence on avian migration patterns. Species traversing such ecological barriers may adopt multiple optimal routes, which can contribute to the formation of migratory divides. From 2018 to 2021, the migration routes of 13 adult Common Cuckoos (Cuculus canorus) breeding in the north of the Qinghai-Tibet Plateau were tracked using satellite transmitters. We found Common Cuckoos have two primary migration routes: western and eastern, respectively following western and eastern edges of the Qinghai-Tibet plateau. The eastern and western routes are likely the optimal routes for the Central Asian Common Cuckoos population to navigate the Qinghai-Tibet Plateau. Furthermore, two individuals exhibited intermediate migration routes, suggesting attempted traverses of the Qinghai-Tibet Plateau, although neither completed the migration. These intermediate routes may indicate migratory behavior influenced by hybridization between eastern and western populations or migratory flexibility. Common Cuckoos exhibit significantly faster migration speed, flight speed, and shorter stopover durations during spring compared to autumn. The observed seasonal differences in migration behavior support birds following time-minimization strategies during spring migration. These results revealed the diverse migration routes of Common Cuckoos shaped by the Qinghai-Tibet Plateau and seasonal variation in migration patterns.
基金Supported by the National Key R&D Program of China project (2017YFC0805309)the National Natural Science Foundation of China (60602020)。
文摘To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.
文摘As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.
基金National Key Research and Development Program(2021YFB2900604)。
文摘Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
基金supported in part by the National Natural Science Foundation of China under Grant U23A20300 and 62072351in part by the Key Research Project of Shaanxi Natural Science Foundation under Grant 2023-JC-ZD-35+1 种基金in part by the Concept Verification Funding of Hangzhou Institute of Technology of Xidian University under Grant GNYZ2024XX007in part by the 111 Project under Grant B16037.
文摘Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.
文摘This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operational characteristics,optimization objectives,vehicle types,and time constraints.Based on literature retrieval results from the Web of Science database,the paper analyzes the current state and trends in VRP research,providing detailed explanations of VRP models and algorithms applied to various scenarios in recent years.Additionally,the article discusses limitations in existing research and provides perspectives on future development trends in VRP research.This review offers researchers in the VRP field a comprehensive overview while identifying future research directions.
文摘This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.
基金Supported by 2024 Planning Project of the China Vocational Education Association"Research and Practice on the Route of Guizhou Vocational Education in Serving the Export of Guizhou Goods Beyond Regional Boundaries in the Context of Rural Revitalization".
文摘This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to contribute to rural revitalization, including the optimization of professional and curriculum systems, the deepening of industry-education integration and school-enterprise cooperation, the enhancement of brand development and marketing efforts, the strengthening of cross-border e-commerce and international cooperation capabilities, and the improvement of policy support and resource allocation systems. The findings aim to provide a theoretical foundation for Guizhou vocational education to support local economic development.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
文摘Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction and expansion projects has gradually become a key measure to improve the service level of the road network and alleviate traffic congestion.Meanwhile,route design is a core aspect of highway reconstruction and expansion projects,and its scientific nature and quality can directly affect the safety,economy,and future operational efficiency of the highway.Therefore,this article provides a detailed analysis of the principles and requirements of route design for highway reconstruction and expansion projects.Additionally,it delves into the design process and key technologies applied in route design for these projects.
基金financially supported by Hunan Provincial Science and Technology Department,China(No.2021JJ10058)Key Research and Development Program of Hunan Province,China(No.2023GK2016)。
文摘A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm and an electro-chemical stability window of 3.8 V.Additionally,an all-solid-state lithium-ion battery using Li_(3)YCl_(3)Br_(3) and LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM811)as the cathode material achieves a capacity retention of 93%after 200 cycles at 0.3C and maintains a specific capacity of 115 mA·h/g during 2C cycling.This exceptional performance is attributed to the high oxidative stability of Li_(3)YCl_(3)Br_(3) and the in-situ formation of Y_(2)O_(3) inert protective layer on the NCM811 surface under high voltage.Consequently,the study demonstrates the feasibility of a simple,cost-effective wet-chemistry route for synthesizing multi-component halides,highlighting its potential for large-scale production of halide solid electrolytes for practical applications.
基金funded by the National Natural Science Foundation of China,grant numbers(62272007,62001007)the Natural Science Foundation of Beijing,grant numbers(4234083,4212018)The authors also extend their appreciation to King Khalid University for funding this work through the Large Group Project under grant number RGP.2/373/45.
文摘Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.
文摘The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF).
基金funded by National Natural Science Foundation of China(No.61741303)Guangxi Natural Science Foundation(No.2017GXNSFAA198161)the Foundation Project of Guangxi Key Laboratory of Spatial Information and Mapping(No.21-238-21-16).
文摘In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing.The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area.Then,the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission.Relay nodes are selected layer by layer,starting from the outermost cluster heads.Finally,the inter-layer routing mechanism is integrated with regional partitioning and clustering methods to develop the WRSN energy optimization algorithm.To further optimize the algorithm’s performance,we conduct parameter optimization experiments on the relay routing selection function,cluster head rotation energy threshold,and inter-layer relay structure selection,ensuring the best configurations for energy efficiency and network lifespan.Based on these optimizations,simulation results demonstrate that the proposed algorithm outperforms traditional forward routing,K-CHRA,and K-CLP algorithms in terms of node mortality rate and energy consumption,extending the number of rounds to 50%node death by 11.9%,19.3%,and 8.3%in a 500-node network,respectively.
文摘Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2023-2-02038).
文摘Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.
文摘Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.
