Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and ...Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
This paper investigates a new SEIQR(susceptible–exposed–infected–quarantined–recovered) epidemic model with quarantine mechanism on heterogeneous complex networks. Firstly, the nonlinear SEIQR epidemic spreading d...This paper investigates a new SEIQR(susceptible–exposed–infected–quarantined–recovered) epidemic model with quarantine mechanism on heterogeneous complex networks. Firstly, the nonlinear SEIQR epidemic spreading dynamic differential coupling model is proposed. Then, by using mean-field theory and the next-generation matrix method, the equilibriums and basic reproduction number are derived. Theoretical results indicate that the basic reproduction number significantly relies on model parameters and topology of the underlying networks. In addition, the globally asymptotic stability of equilibrium and the permanence of the disease are proved in detail by the Routh–Hurwitz criterion, Lyapunov method and La Salle's invariance principle. Furthermore, we find that the quarantine mechanism, that is the quarantine rate(γ1, γ2), has a significant effect on epidemic spreading through sensitivity analysis of basic reproduction number and model parameters. Meanwhile, the optimal control model of quarantined rate and analysis method are proposed, which can optimize the government control strategies and reduce the number of infected individual. Finally, numerical simulations are given to verify the correctness of theoretical results and a practice application is proposed to predict and control the spreading of COVID-19.展开更多
In this paper,a typical experiment is carried out based on a high-resolution air-sea coupled model,namely,the coupled ocean-atmosphere-wave-sediment transport(COAWST)model,on both heterogeneous many-core(SW)and homoge...In this paper,a typical experiment is carried out based on a high-resolution air-sea coupled model,namely,the coupled ocean-atmosphere-wave-sediment transport(COAWST)model,on both heterogeneous many-core(SW)and homogenous multicore(Intel)supercomputing platforms.We construct a hindcast of Typhoon Lekima on both the SW and Intel platforms,compare the simulation results between these two platforms and compare the key elements of the atmospheric and ocean modules to reanalysis data.The comparative experiment in this typhoon case indicates that the domestic many-core computing platform and general cluster yield almost no differences in the simulated typhoon path and intensity,and the differences in surface pressure(PSFC)in the WRF model and sea surface temperature(SST)in the short-range forecast are very small,whereas a major difference can be identified at high latitudes after the first 10 days.Further heat budget analysis verifies that the differences in SST after 10 days are mainly caused by shortwave radiation variations,as influenced by subsequently generated typhoons in the system.These typhoons generated in the hindcast after the first 10 days attain obviously different trajectories between the two platforms.展开更多
This paper demonstrates the use of a commercial simulator as a tool with which to optimize the SAGD （steam-assisted gravity drainage） start-up phase process. The factors affecting the start-up phase are the prime ta...This paper demonstrates the use of a commercial simulator as a tool with which to optimize the SAGD （steam-assisted gravity drainage） start-up phase process. The factors affecting the start-up phase are the prime targets. Among the key investigated factors are wellbore geometry effects, reservoir heterogeneity and circulation phase length. Each of the parameters was investigated via steam chamber development observation along the well pair length and the cross sections in the mid, toe and heel areas. In addition, the cumulative recovery in given time, steam-to-oil ratio and CDOR （calendar day oil rate） production data are used to backup the observations produced in the simulated model. Furthermore, an additional component developed during the research is a statistical modification of a layer cake model with which to create a heterogeneous reservoir to represent real reservoir conditions, based on Monte Carlo＇s simulation.展开更多
In this study, we consider the generation of optimal persistent formations for heterogeneous multi-agent systems, with the leader constraint that only specific agents can act as leaders. We analyze three modes to cont...In this study, we consider the generation of optimal persistent formations for heterogeneous multi-agent systems, with the leader constraint that only specific agents can act as leaders. We analyze three modes to control the optimal persistent formations in two-dimensional space, thereby establishing a model for their constrained generation. Then, we propose an algorithm for generating the optimal persistent formation for heterogeneous multi-agent systems with a leader constraint （LC-HMAS-OPFGA）, which is the exact solution algorithm of the model, and we theoretically prove its validity. This algorithm includes two kernel sub-algorithms, which are optimal persistent graph generating algorithm based on a minimum cost arborescence and the shortest path （MCA-SP-OPGGA）, and the optimal persistent graph adjusting algorithm based on the shortest path （SP-OPGAA）. Under a given agent formation shape and leader constraint, LC-HMAS-OPFGA first generates the network topology and its optimal rigid graph corresponding to this formation shape. Then, LC-HMAS- OPFGA uses MCA-SP-OPGGA to direct the optimal rigid graph to generate the optimal persistent graph. Finally, LC- HMAS-OPFGA uses SP-OPGAA to adjust the optimal persistent graph until it satisfies the leader constraint. We also demonstrate the algorithm, LC-HMAS-OPFGA, with an example and verify its effectiveness.展开更多
On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in m...On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in multilingual environment and formulate corresponding control strategies to reduce the harm caused by rumor propagation.In this paper,considering the multilingual environment and intervention mechanism in the rumor-spreading process,an improved ignorants–spreaders-1–spreaders-2–removers(I2SR)rumor-spreading model with time delay and the nonlinear incidence is established in heterogeneous networks.Firstly,based on the mean-field equations corresponding to the model,the basic reproduction number is derived to ensure the existence of rumor-spreading equilibrium.Secondly,by applying Lyapunov stability theory and graph theory,the global stability of rumor-spreading equilibrium is analyzed in detail.In particular,aiming at the lowest control cost,the optimal control scheme is designed to optimize the intervention mechanism,and the optimal control conditions are derived using the Pontryagin's minimum principle.Finally,some illustrative examples are provided to verify the effectiveness of the theoretical results.The results show that optimizing the intervention mechanism can effectively reduce the densities of spreaders-1 and spreaders-2 within the expected time,which provides guiding insights for public opinion managers to control rumors.展开更多
The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstru...The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.展开更多
This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment ...This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.展开更多
Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic...Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic nature of LEO satellites leads to limited and rapidly varying contact time between them and Earth stations(ESs),making it difficult to timely download massive communication and remote sensing data within the limited time window.To address this challenge in heterogeneous satellite networks with coexisting geostationary-earth-orbit(GEO)and LEO satellites,this paper proposes a dynamic collaborative inter-satellite data download strategy to optimize the long-term weighted energy consumption and data downloads within the constraints of on-board power,backlog stability and time-varying contact.Specifically,the Lyapunov optimization theory is applied to transform the long-term stochastic optimization problem,subject to time-varying contact time and on-board power constraints,into multiple deterministic single time slot problems,based on which online distributed algorithms are developed to enable each satellite to independently obtain the transmit power allocation and data processing decisions in closed-form.Finally,the simulation results demonstrate the superiority of the proposed scheme over benchmarks,e.g.,achieving asymptotic optimality of the weighted energy consumption and data downloads,while maintaining stability of the on-board backlog.展开更多
The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic natu...In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic nature of user locations and the potential of device-to-device(D2D)cooperative caching,limiting the reduction of transmission latency.To address this issue,this paper proposes a joint optimization scheme for edge caching that integrates user mobility prediction with deep reinforcement learning.First,a Transformer-based geolocation prediction model is designed,leveraging multi-head attention mechanisms to capture correlations in historical user trajectories for accurate future location prediction.Then,within a three-tier heterogeneous network,we formulate a latency minimization problem under a D2D cooperative caching architecture and develop a mobility-aware Deep Q-Network(DQN)caching strategy.This strategy takes predicted location information as state input and dynamically adjusts the content distribution across small base stations(SBSs)andmobile users(MUs)to reduce end-to-end delay inmulti-hop content retrieval.Simulation results show that the proposed DQN-based method outperforms other baseline strategies across variousmetrics,achieving a 17.2%reduction in transmission delay compared to DQNmethods withoutmobility integration,thus validating the effectiveness of the joint optimization of location prediction and caching decisions.展开更多
A continuous⁃time distributed optimization was researched for second⁃order heterogeneous multi⁃agent systems.The aim of this study is to keep the velocities of all agents the same and make the velocities converge to t...A continuous⁃time distributed optimization was researched for second⁃order heterogeneous multi⁃agent systems.The aim of this study is to keep the velocities of all agents the same and make the velocities converge to the optimal value to minimize the sum of local cost functions.First,an effective distributed controller which only uses local information was designed.Then,the stability and optimization of the systems were verified.Finally,a simulation case was used to illustrate the analytical results.展开更多
Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malwar...Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malware propagation in this paper.Firstly,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in HWSNs.Secondly,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control theory.Thirdly,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is derived.Finally,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.展开更多
Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in rem...Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in remote areas. Despite the benefits of this network, by increasing the number of users, communication efficiency based on interference management is a major challenge in satellite-based system. Also, the direct links between satellite system and the terrestrial equipment do not always have desirable channel condition. In order to avoid serious throughput degradation, choosing a cooperative relay node is very important. In this paper, Stackelberg game is exploited for interference management that is raised by satellites in down link over terrestrial equipment. Then, for interference management between ground station and relay node with other mobile users, CVX is used to allocate optimum power. Also, the best relay node in this structure is selected based on the harmonic mean function. Thus, the performance of the heterogeneous satellite-cooperative network is investigated based on three benchmarks, namely, successful transmission, energy consumption and outage probability. Finally, the simulation results showed the effect of proposed system model on the performance of next generation satellite networks.展开更多
The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility ...The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.展开更多
Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Trac...Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.展开更多
Cross-media retrieval is an interesting research topic,which seeks to remove the barriers among different modalities.To enable cross-media retrieval,it is needed to find the correlation measures between heterogeneous ...Cross-media retrieval is an interesting research topic,which seeks to remove the barriers among different modalities.To enable cross-media retrieval,it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity.This paper presents a novel approach to learn cross-media correlation between visual features and auditory features for image-audio retrieval.A semi-supervised correlation preserving mapping(SSCPM)method is described to construct the isomorphic SSCPM subspace where canonical correlations between the original visual and auditory features are further preserved.Subspace optimization algorithm is proposed to improve the local image cluster and audio cluster quality in an interactive way.A unique relevance feedback strategy is developed to update the knowledge of cross-media correlation by learning from user behaviors,so retrieval performance is enhanced in a progressive manner.Experimental results show that the performance of our approach is effective.展开更多
A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block pr...A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block probability, the drop probability and the number of users in the heterogeneous networks are calculated in the channel-guard call admission method, and a function of the system benefit which is based on the new call arrival rate and the handoff call arrival rate is proposed. Then the optimal radius of WLAN is obtained by using simulation annealing （SA） method to maximize the benefit. All the nodes should handoff from cellular network to WLAN if they enter WLAN＇s scope and handoff from WLAN to cellular network if they leave the scope. Finally, the algorithm in different new call arrival rates and handoff call arrival rates is analyzed and results show that it can achieve good effects.展开更多
In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and ...In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset.To overcome the challenge of train the big teacher model in resource limited user devices,the digital twin(DT)is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources.Then,during model distillation,each user can update the parameters of its model at either the physical entity or the digital agent.The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming(MIP)problem.To solve the problem,Q-learning and optimization are jointly used,where Q-learning selects models for users and determines whether to train locally or on the server,and optimization is used to allocate resources for users based on the output of Q-learning.Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.展开更多
基金supported by the National Natural Science Foundation of China(724701189072431011).
文摘Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
基金Project supported the Natural Science Foundation of Zhejiang Province, China (Grant No. LQN25F030011)the Fundamental Research Project of Hangzhou Dianzi University (Grant No. KYS065624391)+1 种基金the National Natural Science Foundation of China (Grant No. 61573148)the Science and Technology Planning Project of Guangdong Province, China (Grant No. 2019A050520001)。
文摘This paper investigates a new SEIQR(susceptible–exposed–infected–quarantined–recovered) epidemic model with quarantine mechanism on heterogeneous complex networks. Firstly, the nonlinear SEIQR epidemic spreading dynamic differential coupling model is proposed. Then, by using mean-field theory and the next-generation matrix method, the equilibriums and basic reproduction number are derived. Theoretical results indicate that the basic reproduction number significantly relies on model parameters and topology of the underlying networks. In addition, the globally asymptotic stability of equilibrium and the permanence of the disease are proved in detail by the Routh–Hurwitz criterion, Lyapunov method and La Salle's invariance principle. Furthermore, we find that the quarantine mechanism, that is the quarantine rate(γ1, γ2), has a significant effect on epidemic spreading through sensitivity analysis of basic reproduction number and model parameters. Meanwhile, the optimal control model of quarantined rate and analysis method are proposed, which can optimize the government control strategies and reduce the number of infected individual. Finally, numerical simulations are given to verify the correctness of theoretical results and a practice application is proposed to predict and control the spreading of COVID-19.
基金This work is supported by the National Key Research and Development Plan program of the Ministry of Science and Technology of China(No.2016YFB0201100)Additionally,this work is supported by the National Laboratory for Marine Science and Technology(Qingdao)Major Project of the Aoshan Science and Technology Innovation Program(No.2018ASKJ01-04)the Open Fundation of Key Laboratory of Marine Science and Numerical Simulation,Ministry of Natural Resources(No.2021-YB-02).
文摘In this paper,a typical experiment is carried out based on a high-resolution air-sea coupled model,namely,the coupled ocean-atmosphere-wave-sediment transport(COAWST)model,on both heterogeneous many-core(SW)and homogenous multicore(Intel)supercomputing platforms.We construct a hindcast of Typhoon Lekima on both the SW and Intel platforms,compare the simulation results between these two platforms and compare the key elements of the atmospheric and ocean modules to reanalysis data.The comparative experiment in this typhoon case indicates that the domestic many-core computing platform and general cluster yield almost no differences in the simulated typhoon path and intensity,and the differences in surface pressure(PSFC)in the WRF model and sea surface temperature(SST)in the short-range forecast are very small,whereas a major difference can be identified at high latitudes after the first 10 days.Further heat budget analysis verifies that the differences in SST after 10 days are mainly caused by shortwave radiation variations,as influenced by subsequently generated typhoons in the system.These typhoons generated in the hindcast after the first 10 days attain obviously different trajectories between the two platforms.
文摘This paper demonstrates the use of a commercial simulator as a tool with which to optimize the SAGD （steam-assisted gravity drainage） start-up phase process. The factors affecting the start-up phase are the prime targets. Among the key investigated factors are wellbore geometry effects, reservoir heterogeneity and circulation phase length. Each of the parameters was investigated via steam chamber development observation along the well pair length and the cross sections in the mid, toe and heel areas. In addition, the cumulative recovery in given time, steam-to-oil ratio and CDOR （calendar day oil rate） production data are used to backup the observations produced in the simulated model. Furthermore, an additional component developed during the research is a statistical modification of a layer cake model with which to create a heterogeneous reservoir to represent real reservoir conditions, based on Monte Carlo＇s simulation.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71671059,71401048,71521001,71690230,71690235,and 71472058)the Anhui Provincial Natural Science Foundation,China(Grant No.1508085MG140)
文摘In this study, we consider the generation of optimal persistent formations for heterogeneous multi-agent systems, with the leader constraint that only specific agents can act as leaders. We analyze three modes to control the optimal persistent formations in two-dimensional space, thereby establishing a model for their constrained generation. Then, we propose an algorithm for generating the optimal persistent formation for heterogeneous multi-agent systems with a leader constraint （LC-HMAS-OPFGA）, which is the exact solution algorithm of the model, and we theoretically prove its validity. This algorithm includes two kernel sub-algorithms, which are optimal persistent graph generating algorithm based on a minimum cost arborescence and the shortest path （MCA-SP-OPGGA）, and the optimal persistent graph adjusting algorithm based on the shortest path （SP-OPGAA）. Under a given agent formation shape and leader constraint, LC-HMAS-OPFGA first generates the network topology and its optimal rigid graph corresponding to this formation shape. Then, LC-HMAS- OPFGA uses MCA-SP-OPGGA to direct the optimal rigid graph to generate the optimal persistent graph. Finally, LC- HMAS-OPFGA uses SP-OPGAA to adjust the optimal persistent graph until it satisfies the leader constraint. We also demonstrate the algorithm, LC-HMAS-OPFGA, with an example and verify its effectiveness.
基金the National Natural Science Foundation of People’s Republic of China(Grant Nos.U1703262 and 62163035)the Special Project for Local Science and Technology Development Guided by the Central Government(Grant No.ZYYD2022A05)Xinjiang Key Laboratory of Applied Mathematics(Grant No.XJDX1401)。
文摘On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in multilingual environment and formulate corresponding control strategies to reduce the harm caused by rumor propagation.In this paper,considering the multilingual environment and intervention mechanism in the rumor-spreading process,an improved ignorants–spreaders-1–spreaders-2–removers(I2SR)rumor-spreading model with time delay and the nonlinear incidence is established in heterogeneous networks.Firstly,based on the mean-field equations corresponding to the model,the basic reproduction number is derived to ensure the existence of rumor-spreading equilibrium.Secondly,by applying Lyapunov stability theory and graph theory,the global stability of rumor-spreading equilibrium is analyzed in detail.In particular,aiming at the lowest control cost,the optimal control scheme is designed to optimize the intervention mechanism,and the optimal control conditions are derived using the Pontryagin's minimum principle.Finally,some illustrative examples are provided to verify the effectiveness of the theoretical results.The results show that optimizing the intervention mechanism can effectively reduce the densities of spreaders-1 and spreaders-2 within the expected time,which provides guiding insights for public opinion managers to control rumors.
基金National Natural Science Foundation of China(52261032,51861021,51661016)Science and Technology Plan of Gansu Province(21YF5GA074)+2 种基金Public Welfare Project of Zhejiang Natural Science Foundation(LGG22E010008)Wenzhou Basic Public Welfare Scientific Research Project(G2023020)Incubation Program of Excellent Doctoral Dissertation-Lanzhou University of Technology。
文摘The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.
基金supported by the National Natural Science Foundation of China(61971470).
文摘This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant 62371098the National Key Laboratory ofWireless Communications Foundation under Grant IFN20230203the National Key Research and Development Program of China under Grant 2021YFB2900404.
文摘Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic nature of LEO satellites leads to limited and rapidly varying contact time between them and Earth stations(ESs),making it difficult to timely download massive communication and remote sensing data within the limited time window.To address this challenge in heterogeneous satellite networks with coexisting geostationary-earth-orbit(GEO)and LEO satellites,this paper proposes a dynamic collaborative inter-satellite data download strategy to optimize the long-term weighted energy consumption and data downloads within the constraints of on-board power,backlog stability and time-varying contact.Specifically,the Lyapunov optimization theory is applied to transform the long-term stochastic optimization problem,subject to time-varying contact time and on-board power constraints,into multiple deterministic single time slot problems,based on which online distributed algorithms are developed to enable each satellite to independently obtain the transmit power allocation and data processing decisions in closed-form.Finally,the simulation results demonstrate the superiority of the proposed scheme over benchmarks,e.g.,achieving asymptotic optimality of the weighted energy consumption and data downloads,while maintaining stability of the on-board backlog.
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
基金supported by the Liaoning Provincial Education Department Fund,grant number JYTZD2023083.
文摘In dynamic 5G network environments,user mobility and heterogeneous network topologies pose dual challenges to the effort of improving performance of mobile edge caching.Existing studies often overlook the dynamic nature of user locations and the potential of device-to-device(D2D)cooperative caching,limiting the reduction of transmission latency.To address this issue,this paper proposes a joint optimization scheme for edge caching that integrates user mobility prediction with deep reinforcement learning.First,a Transformer-based geolocation prediction model is designed,leveraging multi-head attention mechanisms to capture correlations in historical user trajectories for accurate future location prediction.Then,within a three-tier heterogeneous network,we formulate a latency minimization problem under a D2D cooperative caching architecture and develop a mobility-aware Deep Q-Network(DQN)caching strategy.This strategy takes predicted location information as state input and dynamically adjusts the content distribution across small base stations(SBSs)andmobile users(MUs)to reduce end-to-end delay inmulti-hop content retrieval.Simulation results show that the proposed DQN-based method outperforms other baseline strategies across variousmetrics,achieving a 17.2%reduction in transmission delay compared to DQNmethods withoutmobility integration,thus validating the effectiveness of the joint optimization of location prediction and caching decisions.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61573199 and 61571441)。
文摘A continuous⁃time distributed optimization was researched for second⁃order heterogeneous multi⁃agent systems.The aim of this study is to keep the velocities of all agents the same and make the velocities converge to the optimal value to minimize the sum of local cost functions.First,an effective distributed controller which only uses local information was designed.Then,the stability and optimization of the systems were verified.Finally,a simulation case was used to illustrate the analytical results.
基金National Natural Science Foundation of China(No.61772018)Zhejiang Provincial Natural Science Foundation of China(No.LZ22F020002)。
文摘Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malware propagation in this paper.Firstly,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in HWSNs.Secondly,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control theory.Thirdly,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is derived.Finally,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.
文摘Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in remote areas. Despite the benefits of this network, by increasing the number of users, communication efficiency based on interference management is a major challenge in satellite-based system. Also, the direct links between satellite system and the terrestrial equipment do not always have desirable channel condition. In order to avoid serious throughput degradation, choosing a cooperative relay node is very important. In this paper, Stackelberg game is exploited for interference management that is raised by satellites in down link over terrestrial equipment. Then, for interference management between ground station and relay node with other mobile users, CVX is used to allocate optimum power. Also, the best relay node in this structure is selected based on the harmonic mean function. Thus, the performance of the heterogeneous satellite-cooperative network is investigated based on three benchmarks, namely, successful transmission, energy consumption and outage probability. Finally, the simulation results showed the effect of proposed system model on the performance of next generation satellite networks.
基金supported by the National Natural Science Foundation of China (No. 61741102, No. 61471164)China Scholarship Council
文摘The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.
基金the National Key Research and Development Plan,China(No.2019YFB1706502)the National Natural Science Foundation of China(Nos.62003366,12102077,12072059)+1 种基金the China Postdoctoral Science Foundation(No.2020M670744)the Natural Science Foundation of Liaoning Province,China(No.2010-ZD-0021)。
文摘Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.
基金Project supported by the National Natural Science Foundation of China (Nos. 60533090 and 60773051)the Natural Science Foundation of Zhejiang Province (No. Y105395),China
文摘Cross-media retrieval is an interesting research topic,which seeks to remove the barriers among different modalities.To enable cross-media retrieval,it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity.This paper presents a novel approach to learn cross-media correlation between visual features and auditory features for image-audio retrieval.A semi-supervised correlation preserving mapping(SSCPM)method is described to construct the isomorphic SSCPM subspace where canonical correlations between the original visual and auditory features are further preserved.Subspace optimization algorithm is proposed to improve the local image cluster and audio cluster quality in an interactive way.A unique relevance feedback strategy is developed to update the knowledge of cross-media correlation by learning from user behaviors,so retrieval performance is enhanced in a progressive manner.Experimental results show that the performance of our approach is effective.
文摘A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks （WLANs）. Firstly the block probability, the drop probability and the number of users in the heterogeneous networks are calculated in the channel-guard call admission method, and a function of the system benefit which is based on the new call arrival rate and the handoff call arrival rate is proposed. Then the optimal radius of WLAN is obtained by using simulation annealing （SA） method to maximize the benefit. All the nodes should handoff from cellular network to WLAN if they enter WLAN＇s scope and handoff from WLAN to cellular network if they leave the scope. Finally, the algorithm in different new call arrival rates and handoff call arrival rates is analyzed and results show that it can achieve good effects.
基金supported by the National Key Research and Development Program of China (2020YFB1807700)the National Natural Science Foundation of China (NSFC)under Grant No.62071356the Chongqing Key Laboratory of Mobile Communications Technology under Grant cqupt-mct202202。
文摘In this paper,to deal with the heterogeneity in federated learning(FL)systems,a knowledge distillation(KD)driven training framework for FL is proposed,where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset.To overcome the challenge of train the big teacher model in resource limited user devices,the digital twin(DT)is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources.Then,during model distillation,each user can update the parameters of its model at either the physical entity or the digital agent.The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming(MIP)problem.To solve the problem,Q-learning and optimization are jointly used,where Q-learning selects models for users and determines whether to train locally or on the server,and optimization is used to allocate resources for users based on the output of Q-learning.Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.
