As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expo...As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expose vehicles to malicious external attacks,resulting in information loss or even tampering,thereby creating serious security vulnerabilities.Blockchain technology can maintain a shared ledger among servers.In the Raft consensus mechanism,as long as more than half of the nodes remain operational,the system will not collapse,effectively maintaining the system’s robustness and security.To protect vehicle information,we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing.To address the additional latency introduced by blockchain,we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency,ensuring that the system meets the requirements for low latency and high reliability.Simulation results demonstrate that the optimized data extraction rate significantly reduces systemdelay,with relatively stable variations in latency.Moreover,the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments,such as 5G and next-generation smart city systems.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing...This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.展开更多
As the proportion of natural gas consumption in the energy market gradually increases,optimizing the design of gas storage surface system(GSSS)has become a current research focus.Existing studies on the two independen...As the proportion of natural gas consumption in the energy market gradually increases,optimizing the design of gas storage surface system(GSSS)has become a current research focus.Existing studies on the two independent injection pipeline network(InNET)and production pipeline network(ProNET)for underground natural gas storage(UNGS)are scarce,and no optimization methods have been proposed yet.Therefore,this paper focuses on the flow and pressure boundary characteristics of the GSSS.It constructs systematic models,including the injection multi-condition coupled model(INM model),production multi-condition coupled model(PRM model),injection single condition model(INS model)and production single condition model(PRS model)to optimize the design parameters.Additionally,this paper proposes a hybrid genetic algorithm based on generalized reduced gradient(HGA-GRG)for solving the models.The models and algorithm are applied to a case study with the objective of minimizing the cost of the pipeline network.For the GSSS,nine different condition scenarios are considered,and iterative process analysis and sensitivity analysis of these scenarios are conducted.Moreover,simulation scenarios are set up to verify the applicability of different scenarios to the boundaries.The research results show that the cost of the InNET considering the coupled pressure boundary is 64.4890×10^(4) CNY,and the cost of the ProNET considering coupled flow and pressure boundaries is 87.7655×10^(4) CNY,demonstrating greater applicability and economy than those considering only one or two types of conditions.The algorithms and models proposed in this paper provide an effective means for the design of parameters for GSSS.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
This article presents a systematic direct approach to carry out effective optimization of a wide range of continuous-thrust Earth-orbit transfers with intermediate-level thrust acceleration,including minimum-time (wit...This article presents a systematic direct approach to carry out effective optimization of a wide range of continuous-thrust Earth-orbit transfers with intermediate-level thrust acceleration,including minimum-time (with a single burn arc) and mini-mum-fuel (with multiple burn arcs) transfers. With direct control parameterization,in which the control steering programs of burn arcs are interpolated through a finite number of nodes,the optimal control problem is converted into the parameter optimi-zation proble...展开更多
Optimal use of water and fertilizers can enhance winter wheat yield and increase the efficiencies of water and fertilizer usage in dryland agricultural systems. In order to optimize water and nitrogen （N） management...Optimal use of water and fertilizers can enhance winter wheat yield and increase the efficiencies of water and fertilizer usage in dryland agricultural systems. In order to optimize water and nitrogen （N） management for winter wheat, we conducted field experiments from 2006 to 2008 at the Changwu Agro-ecological Experimental Station of the Chinese Academy of Sciences on the Loess Plateau, China. Regression models of wheat yield and evapotranspiration （ET） were established in this study to evaluate the water and fertilizer coupling effects and to determine the optimal coupling domain. The results showed that there was a positive effect of water and N fertilizer on crop yield, and optimal irrigation and N inputs can significantly increase the yield of winter wheat. In the drought year （2006-2007）, the maximum yield （Yma~） of winter wheat was 9.211 t/hm2 for the treatment with 324 mm irriga- tion and 310 kg/hm2 N input, and the highest water use efficiency （WUE） of 16.335 kg/（hm2.mm） was achieved with 198 mm irrigation and 274 kg/hm2 N input. While in the normal year （2007-2008）, the maximum winter wheat yield of 10.715 t/hm2 was achieved by applying 318 mm irrigation and 291 kg/hm2 N, and the highest WUE was 18.69 kg/（hm2.mm） with 107 mm irrigation and 256 kg/hm2 N input. Crop yield and ET response to irrigation and N inputs followed a quadratic and a line function, respectively. The optimal coupling domain was determined using the elas- ticity index （El） and its expression in the water-N dimensions, and was represented by an ellipse, such that the global maximum WUE （WUErnax） and Ymax values corresponded to the left and right end points of the long axis, respectively. Considering the aim to get the greatest profit in practice, the optimal coupling domain was represented by the lower half of the ellipse, with the Yma~ and WUE^ax on the two end points of the long axis. Overall, we found that the total amount of irrigation for winter wheat should not exceed 324 ram. In addition, our optimal coupling domain visually reflects the optimal range of water and N inputs for the maximum winter wheat yield on the Loess Plateau, and it may also provide a useful reference for identifying appropriate water and N inputs in agricultural applications.展开更多
The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performari...The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.展开更多
A control system aims at vibration reduction in a two-span rotor system with two shear mode magnetorheological （MRF） dampers is designed. A finite element model of the MRF damper- rotor system is built and used to a...A control system aims at vibration reduction in a two-span rotor system with two shear mode magnetorheological （MRF） dampers is designed. A finite element model of the MRF damper- rotor system is built and used to analyze the rotor vibration characteristics. Based on Hooke and Jeeves algorithm and the numerical simulation analysis, an optimal appropriate controller is proposed and designed. Experimental results show that rotor vibration caused by unbalance is well controlled （ first critical speed region 37% , second critical speed region 42% ）. To reflect advantages of optimi- zing strategy presented and validate the intelligent optimization control technology, detailed experi- ments were developed on a two-span rotor-vibration-control platform. The influence on accuracy, rapidity and stability of optimizing control for rotor vibration are analyzed. It provides a powerful technical support for the extension and application in target and control for shafting vibration.展开更多
A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundationa...A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundational principle,is presented. According to the principle,an ammonia compressor,whose working conditions are based on key operational parameters of the whole ammoniarecovery system, is the mainly energy-consumption part of ammonia-recovery system in the modified equipment of flax fiber. A generally mathematical model based on work efficiency of an ammonia compressor is founded,which is available to rate effective work and energy consumption of the ammonia compressor. The optimum operation-efficiency of the ammonia compressor is chosen as the goal to analyze and calculate the key operational parameters of the ammonia-recovery system. In the above analyzing and calculating,a mathematical model on ammonia flowing from the reactor to the register 1 is developed,in order to provide further understanding of the principle of an ammonia-recovery system. At the meantime,the ammonia flow regime in the pipeline and the process of ammonia inflation and deflation from the reactor to the register 1 are taken separately into account in the model. An iterative method is for obtaining parametric solutions of the mathematical model on ammonia flowing from the reactor to the register 1 and the key operational parameters of the ammoniarecovery system. A parametric analysis is put forward to complete showing the ammonia velocity or the state of the reactor and the register 1. The key optimized parameters will be achieved in term of the minimum efficiency after comparing the work efficiencies of an ammonia compressor at different working conditions.展开更多
The result merging for multiple Independent Resource Retrieval Systems (IRRSs), which is a key component in developing a meta-search engine, is a difficult problem that still not effectively solved. Most of the existi...The result merging for multiple Independent Resource Retrieval Systems (IRRSs), which is a key component in developing a meta-search engine, is a difficult problem that still not effectively solved. Most of the existing result merging methods, usually suffered a great influence from the usefulness weight of different IRRS results and overlap rate among them. In this paper, we proposed a scheme that being capable of coalescing and optimizing a group of existing multi-sources-retrieval merging results effectively by Discrete Particle Swarm Optimization (DPSO). The experimental results show that the DPSO, not only can overall outperform all the other result merging algorithms it employed, but also has better adaptability in application for unnecessarily taking into account different IRRS's usefulness weight and their overlap rate with respect to a concrete query. Compared to other result merging algorithms it employed, the DPSO's recognition precision can increase nearly 24.6%, while the precision standard deviation for different queries can decrease about 68.3%.展开更多
At present, there are some static code analyses and optimizations that can be applied to Concurrent C programs to improve their performance or verify their logical correctness. These analyses and optimizations are int...At present, there are some static code analyses and optimizations that can be applied to Concurrent C programs to improve their performance or verify their logical correctness. These analyses and optimizations are inter-process. In order to make their implementation easy, we propose a new method to construct an optimizing compiling system CCOC for Concurrent C. CCOC supports inter-process code analysis and optimization to Concurrent C programs and does not affect the system's portability and separate compilation of source programs. We also discuss some implementation details of CCOC briefly.展开更多
The three levels optimizing strategy is put forward for the networked manufacturing resources optimizing configuration, namely, the optimizing of a logical manufacturing process, the optimizing of simulation-based int...The three levels optimizing strategy is put forward for the networked manufacturing resources optimizing configuration, namely, the optimizing of a logical manufacturing process, the optimizing of simulation-based integration of process planning and scheduling, and the optimizing of networked production scheduling. Then, the web services-based architecture of networked manufacturing resources optimizing configuration is brought forward. Finally, the key algorithm of the networked manufacturing resources optimizing configuration is discussed, namely, the two phases manufacturing partners selection method, which including the group technology-based manufacturing resources pre-configuration and the genetic algorithm-based executable manufacturing process optimizing.展开更多
Thermal energy storage (TES) can increase the energetic efficiencies and, in many cases, the exergetic efficiencies of thermal energy systems. Steam boiler plant with a violently fluctuating load is a typical example ...Thermal energy storage (TES) can increase the energetic efficiencies and, in many cases, the exergetic efficiencies of thermal energy systems. Steam boiler plant with a violently fluctuating load is a typical example when a steam accumulator is added to it. While the conparatively big first cost constitutes a barrier to the wide use of TES, the cost will notably be reduced through minimizing the necessary thermal capacity of it JThe structure and illustrations are given for the computer program designed for performing the optimization. This'program was applied to an existing boiler plant equipped with a steam accumulator. The results show that there would have been a big reduction in the necessary capacity, if the design of this steam accumulator had been optimized. Four conclusions have been reached.展开更多
Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
In this work, we show that when there is insufficient equipment for detecting a disease whose prevalence is t% in a sub-population of size N, it is optimal to divide the N samples into n groups of size r each and then...In this work, we show that when there is insufficient equipment for detecting a disease whose prevalence is t% in a sub-population of size N, it is optimal to divide the N samples into n groups of size r each and then, the value <img src="Edit_ce149849-3742-48fe-820b-02ccc0c92d83.bmp" alt="" /> allows systematic screening of all N individuals by performing less than N tests (In this expression, <img src="Edit_987eb236-a883-4894-ba2d-52bde5f35056.bmp" alt="" /> represents the floor function<sup>1</sup> of x ∈ R). Based on this result and on certain functions of the R software, we subsequently propose a probabilistic strategy capable of optimizing the screening tests under certain conditions.展开更多
By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and ...By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.展开更多
Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues.This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal va...Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues.This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal vapor compression(MED-TVC)system,a highly promising desalination technology.The MED-TVC system presents an energy-efficient approach to desalination by harnessing waste heat sources and incorporating thermal vapor compression.The primary objective of this research is to assess the system’s thermodynamic efficiency and environmental impact,considering both energy and exergy aspects.The investigation delves into the intricacies of energy and exergy losses within the MED-TVC process,providing a holistic understanding of its performance.By scrutinizing the distribution and sources of exergy destruction,the study identifies specific areas for enhancement in the system’s design and operation,thereby elevating its overall sustainability.Moreover,the exergoenvironmental analysis quantifies the environmental impact,offering vital insights into the sustainability of seawater desalination technologies.The results underscore the significance of every component in the MED-TVC system for its exergoenvironmental performance.Notably,the thermal vapor compressor emerges as pivotal due to its direct impact on energy efficiency,exergy losses,and the environmental footprint of the process.Consequently,optimizing this particular component becomes imperative for achieving a more sustainable and efficient desalination system.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.61701197in part by the National Key Research and Development Program of China under Grant No.2021YFA1000500(4)in part by the 111 project under Grant No.B23008.
文摘As Internet of Vehicles(IoV)technology continues to advance,edge computing has become an important tool for assisting vehicles in handling complex tasks.However,the process of offloading tasks to edge servers may expose vehicles to malicious external attacks,resulting in information loss or even tampering,thereby creating serious security vulnerabilities.Blockchain technology can maintain a shared ledger among servers.In the Raft consensus mechanism,as long as more than half of the nodes remain operational,the system will not collapse,effectively maintaining the system’s robustness and security.To protect vehicle information,we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing.To address the additional latency introduced by blockchain,we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency,ensuring that the system meets the requirements for low latency and high reliability.Simulation results demonstrate that the optimized data extraction rate significantly reduces systemdelay,with relatively stable variations in latency.Moreover,the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments,such as 5G and next-generation smart city systems.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.
基金funded by the National Natural Science Foun-dation of China,grant number 51704253 and 52474084。
文摘As the proportion of natural gas consumption in the energy market gradually increases,optimizing the design of gas storage surface system(GSSS)has become a current research focus.Existing studies on the two independent injection pipeline network(InNET)and production pipeline network(ProNET)for underground natural gas storage(UNGS)are scarce,and no optimization methods have been proposed yet.Therefore,this paper focuses on the flow and pressure boundary characteristics of the GSSS.It constructs systematic models,including the injection multi-condition coupled model(INM model),production multi-condition coupled model(PRM model),injection single condition model(INS model)and production single condition model(PRS model)to optimize the design parameters.Additionally,this paper proposes a hybrid genetic algorithm based on generalized reduced gradient(HGA-GRG)for solving the models.The models and algorithm are applied to a case study with the objective of minimizing the cost of the pipeline network.For the GSSS,nine different condition scenarios are considered,and iterative process analysis and sensitivity analysis of these scenarios are conducted.Moreover,simulation scenarios are set up to verify the applicability of different scenarios to the boundaries.The research results show that the cost of the InNET considering the coupled pressure boundary is 64.4890×10^(4) CNY,and the cost of the ProNET considering coupled flow and pressure boundaries is 87.7655×10^(4) CNY,demonstrating greater applicability and economy than those considering only one or two types of conditions.The algorithms and models proposed in this paper provide an effective means for the design of parameters for GSSS.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金National Natural Science Foundation of China (10603005)Foundation of President of the Academy of Opto-Electro-nics ( AOE-CX-200601)
文摘This article presents a systematic direct approach to carry out effective optimization of a wide range of continuous-thrust Earth-orbit transfers with intermediate-level thrust acceleration,including minimum-time (with a single burn arc) and mini-mum-fuel (with multiple burn arcs) transfers. With direct control parameterization,in which the control steering programs of burn arcs are interpolated through a finite number of nodes,the optimal control problem is converted into the parameter optimi-zation proble...
基金National Natural Science Foundation of China (51239009)National Science and Technology Support Program of China (2011BAD29B05)+1 种基金Key Discipline Foundation of Water Resources and Hydropower Engineering of Xinjiang Province (XJZDXK-2002-10-05)Natural Science Foundation of Shandong Province (ZR2010EM042)
文摘Optimal use of water and fertilizers can enhance winter wheat yield and increase the efficiencies of water and fertilizer usage in dryland agricultural systems. In order to optimize water and nitrogen （N） management for winter wheat, we conducted field experiments from 2006 to 2008 at the Changwu Agro-ecological Experimental Station of the Chinese Academy of Sciences on the Loess Plateau, China. Regression models of wheat yield and evapotranspiration （ET） were established in this study to evaluate the water and fertilizer coupling effects and to determine the optimal coupling domain. The results showed that there was a positive effect of water and N fertilizer on crop yield, and optimal irrigation and N inputs can significantly increase the yield of winter wheat. In the drought year （2006-2007）, the maximum yield （Yma~） of winter wheat was 9.211 t/hm2 for the treatment with 324 mm irriga- tion and 310 kg/hm2 N input, and the highest water use efficiency （WUE） of 16.335 kg/（hm2.mm） was achieved with 198 mm irrigation and 274 kg/hm2 N input. While in the normal year （2007-2008）, the maximum winter wheat yield of 10.715 t/hm2 was achieved by applying 318 mm irrigation and 291 kg/hm2 N, and the highest WUE was 18.69 kg/（hm2.mm） with 107 mm irrigation and 256 kg/hm2 N input. Crop yield and ET response to irrigation and N inputs followed a quadratic and a line function, respectively. The optimal coupling domain was determined using the elas- ticity index （El） and its expression in the water-N dimensions, and was represented by an ellipse, such that the global maximum WUE （WUErnax） and Ymax values corresponded to the left and right end points of the long axis, respectively. Considering the aim to get the greatest profit in practice, the optimal coupling domain was represented by the lower half of the ellipse, with the Yma~ and WUE^ax on the two end points of the long axis. Overall, we found that the total amount of irrigation for winter wheat should not exceed 324 ram. In addition, our optimal coupling domain visually reflects the optimal range of water and N inputs for the maximum winter wheat yield on the Loess Plateau, and it may also provide a useful reference for identifying appropriate water and N inputs in agricultural applications.
基金Project (No. 2008AA06A413) supported by the National High-Tech R&D (863) Program of China
文摘The differential evolution （DE） algorithm has been received increasing attention in terms of optimizing the design for the water distribution systems （WDSs）. This paper aims to carry out a comprehensive performarice comparison between the new emerged DE algorithm and the most popular algorithm-the genetic algorithm （GA）. A total of six benchmark WDS case studies were used with the number of decision variables ranging from 8 to 454. A preliminary sensitivity analysis was performed to select the most effective parameter values for both algorithms to enable the fair comparison. It is observed from the results that the DE algorithm consistently outperforms the GA in terms of both efficiency and the solution quality for each case study. Additionally, the DE algorithm was also compared with the previously published optimization algorithms based on the results for those six case studies, indicating that the DE exhibits comparable performance with other algorithms. It can be concluded that the DE is a newly promising optimization algorithm in the design of WDSs.
基金Supported by the National Program on Key Basic Research Project(973Program)(2012CB026000)Ph.D Programs Foundation of Ministry of Education of China(20110010110009)
文摘A control system aims at vibration reduction in a two-span rotor system with two shear mode magnetorheological （MRF） dampers is designed. A finite element model of the MRF damper- rotor system is built and used to analyze the rotor vibration characteristics. Based on Hooke and Jeeves algorithm and the numerical simulation analysis, an optimal appropriate controller is proposed and designed. Experimental results show that rotor vibration caused by unbalance is well controlled （ first critical speed region 37% , second critical speed region 42% ）. To reflect advantages of optimi- zing strategy presented and validate the intelligent optimization control technology, detailed experi- ments were developed on a two-span rotor-vibration-control platform. The influence on accuracy, rapidity and stability of optimizing control for rotor vibration are analyzed. It provides a powerful technical support for the extension and application in target and control for shafting vibration.
基金National Science and Technology Support Program,China(No.2012BAF13B03)Program of Shanghai Subject Chief Scientist,China(No.12XD1420300)
文摘A detailed analysis of operational process and principle of ammonia-recovery system in the modified equipment of flax fiber,which will be applied to parameters optimizing of the ammoniarecovery system as a foundational principle,is presented. According to the principle,an ammonia compressor,whose working conditions are based on key operational parameters of the whole ammoniarecovery system, is the mainly energy-consumption part of ammonia-recovery system in the modified equipment of flax fiber. A generally mathematical model based on work efficiency of an ammonia compressor is founded,which is available to rate effective work and energy consumption of the ammonia compressor. The optimum operation-efficiency of the ammonia compressor is chosen as the goal to analyze and calculate the key operational parameters of the ammonia-recovery system. In the above analyzing and calculating,a mathematical model on ammonia flowing from the reactor to the register 1 is developed,in order to provide further understanding of the principle of an ammonia-recovery system. At the meantime,the ammonia flow regime in the pipeline and the process of ammonia inflation and deflation from the reactor to the register 1 are taken separately into account in the model. An iterative method is for obtaining parametric solutions of the mathematical model on ammonia flowing from the reactor to the register 1 and the key operational parameters of the ammoniarecovery system. A parametric analysis is put forward to complete showing the ammonia velocity or the state of the reactor and the register 1. The key optimized parameters will be achieved in term of the minimum efficiency after comparing the work efficiencies of an ammonia compressor at different working conditions.
基金Supported by the National Natural Science Foundation of China (No. 90818007)
文摘The result merging for multiple Independent Resource Retrieval Systems (IRRSs), which is a key component in developing a meta-search engine, is a difficult problem that still not effectively solved. Most of the existing result merging methods, usually suffered a great influence from the usefulness weight of different IRRS results and overlap rate among them. In this paper, we proposed a scheme that being capable of coalescing and optimizing a group of existing multi-sources-retrieval merging results effectively by Discrete Particle Swarm Optimization (DPSO). The experimental results show that the DPSO, not only can overall outperform all the other result merging algorithms it employed, but also has better adaptability in application for unnecessarily taking into account different IRRS's usefulness weight and their overlap rate with respect to a concrete query. Compared to other result merging algorithms it employed, the DPSO's recognition precision can increase nearly 24.6%, while the precision standard deviation for different queries can decrease about 68.3%.
文摘At present, there are some static code analyses and optimizations that can be applied to Concurrent C programs to improve their performance or verify their logical correctness. These analyses and optimizations are inter-process. In order to make their implementation easy, we propose a new method to construct an optimizing compiling system CCOC for Concurrent C. CCOC supports inter-process code analysis and optimization to Concurrent C programs and does not affect the system's portability and separate compilation of source programs. We also discuss some implementation details of CCOC briefly.
基金This paper is supported by National High-Tech R&D Program for CIMS, China (Grant No. 2003AA411110) theNational Research Foundation for Doctoral Program of Higher Education, China (Grant No. 20040699025).
文摘The three levels optimizing strategy is put forward for the networked manufacturing resources optimizing configuration, namely, the optimizing of a logical manufacturing process, the optimizing of simulation-based integration of process planning and scheduling, and the optimizing of networked production scheduling. Then, the web services-based architecture of networked manufacturing resources optimizing configuration is brought forward. Finally, the key algorithm of the networked manufacturing resources optimizing configuration is discussed, namely, the two phases manufacturing partners selection method, which including the group technology-based manufacturing resources pre-configuration and the genetic algorithm-based executable manufacturing process optimizing.
文摘Thermal energy storage (TES) can increase the energetic efficiencies and, in many cases, the exergetic efficiencies of thermal energy systems. Steam boiler plant with a violently fluctuating load is a typical example when a steam accumulator is added to it. While the conparatively big first cost constitutes a barrier to the wide use of TES, the cost will notably be reduced through minimizing the necessary thermal capacity of it JThe structure and illustrations are given for the computer program designed for performing the optimization. This'program was applied to an existing boiler plant equipped with a steam accumulator. The results show that there would have been a big reduction in the necessary capacity, if the design of this steam accumulator had been optimized. Four conclusions have been reached.
基金supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
文摘In this work, we show that when there is insufficient equipment for detecting a disease whose prevalence is t% in a sub-population of size N, it is optimal to divide the N samples into n groups of size r each and then, the value <img src="Edit_ce149849-3742-48fe-820b-02ccc0c92d83.bmp" alt="" /> allows systematic screening of all N individuals by performing less than N tests (In this expression, <img src="Edit_987eb236-a883-4894-ba2d-52bde5f35056.bmp" alt="" /> represents the floor function<sup>1</sup> of x ∈ R). Based on this result and on certain functions of the R software, we subsequently propose a probabilistic strategy capable of optimizing the screening tests under certain conditions.
基金supported by State Grid Information and Telecommunication Group Scientific and Technological Innovation Project“Research on Power Digital Space Technology System and Key Technologies”(Program No.SGIT0000XMJS2310456).
文摘By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.
基金the Biomaterials and Transport Phenomena Laboratory Agreement No.30303-12-2003,at the University of Medea.
文摘Seawater desalination stands as an increasingly indispensable solution to address global water scarcity issues.This study conducts a thorough exergoenvironmental analysis of a multi-effect distillation with thermal vapor compression(MED-TVC)system,a highly promising desalination technology.The MED-TVC system presents an energy-efficient approach to desalination by harnessing waste heat sources and incorporating thermal vapor compression.The primary objective of this research is to assess the system’s thermodynamic efficiency and environmental impact,considering both energy and exergy aspects.The investigation delves into the intricacies of energy and exergy losses within the MED-TVC process,providing a holistic understanding of its performance.By scrutinizing the distribution and sources of exergy destruction,the study identifies specific areas for enhancement in the system’s design and operation,thereby elevating its overall sustainability.Moreover,the exergoenvironmental analysis quantifies the environmental impact,offering vital insights into the sustainability of seawater desalination technologies.The results underscore the significance of every component in the MED-TVC system for its exergoenvironmental performance.Notably,the thermal vapor compressor emerges as pivotal due to its direct impact on energy efficiency,exergy losses,and the environmental footprint of the process.Consequently,optimizing this particular component becomes imperative for achieving a more sustainable and efficient desalination system.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
