侦察星座优化是天基信息体系建设的关键问题。为弥补以往研究大多只采用少量性能指标进行侦察星座优化的不足,提出了一种综合考虑5项性能指标的侦察星座优化模型。在解算优化模型过程中,为解决传统基于Pareto支配的进化算法出现的选择...侦察星座优化是天基信息体系建设的关键问题。为弥补以往研究大多只采用少量性能指标进行侦察星座优化的不足,提出了一种综合考虑5项性能指标的侦察星座优化模型。在解算优化模型过程中,为解决传统基于Pareto支配的进化算法出现的选择压力与多样性不足的问题,提出了TOPSIS-MOPSO(Technique for Order Preference by Similarity to an Ideal Solution-Multi-Objective Particle Swarm Optimization)算法,将多属性决策领域的TOPSIS引入进化算法中,并与SPD(Strengthened Pareto Dominate)相结合,得到一种能够同时增强种群收敛性与多样性的环境选择策略。提出了基于Harmonic距离的全局最优粒子选择策略,加快种群收敛速度,保护种群多样性;提出了自适应进化算子选择策略,帮助算法摆脱局部最优解。将TOPSIS-MOPSO算法应用在侦察星座优化问题上,并与MOPSO、DGEA、AR-MOEA 3种经典方法进行实验对比分析,实验结果显示,所提算法比其他3种算法在Δ*、IGD和HV上的最优指标值分别提升了19.76%、89.07%和28.2%。展开更多
Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)sig...Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.展开更多
Large high clearance self-propelled sprayers were widely used in field plant protection due to their high-efficiency operation capabilities.Influenced by the characteristics of field operations such as high power,heav...Large high clearance self-propelled sprayers were widely used in field plant protection due to their high-efficiency operation capabilities.Influenced by the characteristics of field operations such as high power,heavy weight,high ground clearance,and fast operation speed,the comprehensive requirements for the ride comfort,handling stability and road friendliness of the sprayer were increasingly strong.At the present stage,the chassis structure of the high clearance selfpropelled sprayer that attaches great importance to the improvement of comprehensive performance still has the problems of severe bumps,weak handling performance and serious road damage in complex field environments.Therefore,this paper proposes an optimization design method for hydro-pneumatic suspension system of a high clearance self-propelled sprayer based on the improved MOPSO(Multi-Objective Particle Swarm Optimization)algorithm,covering the entire process of configuration design,parameter intelligent optimization,and system verification of the high clearance self-propelled sprayer chassis.Specifically,chassis structure of the hydro-pneumatic suspension suitable for the high clearance self-propelled sprayer was designed,and a design method combining the improved MOPSO algorithm based on time-varying fusion strategy and adaptive update with the parameter optimization of hydro-pneumatic suspension based on this algorithm was proposed,and finally the software simulation and bench performance verification were carried out.The results show that the optimized hydropneumatic suspension has excellent vibration reduction effect,and the body acceleration,suspension dynamic deflection and tire deflection were increased by 16.5%,9.9%and 0.9%respectively,compared with those before optimization.The comprehensive performance of the hydro-pneumatic suspension designed in this study is better than that of the traditional suspension.展开更多
文摘侦察星座优化是天基信息体系建设的关键问题。为弥补以往研究大多只采用少量性能指标进行侦察星座优化的不足,提出了一种综合考虑5项性能指标的侦察星座优化模型。在解算优化模型过程中,为解决传统基于Pareto支配的进化算法出现的选择压力与多样性不足的问题,提出了TOPSIS-MOPSO(Technique for Order Preference by Similarity to an Ideal Solution-Multi-Objective Particle Swarm Optimization)算法,将多属性决策领域的TOPSIS引入进化算法中,并与SPD(Strengthened Pareto Dominate)相结合,得到一种能够同时增强种群收敛性与多样性的环境选择策略。提出了基于Harmonic距离的全局最优粒子选择策略,加快种群收敛速度,保护种群多样性;提出了自适应进化算子选择策略,帮助算法摆脱局部最优解。将TOPSIS-MOPSO算法应用在侦察星座优化问题上,并与MOPSO、DGEA、AR-MOEA 3种经典方法进行实验对比分析,实验结果显示,所提算法比其他3种算法在Δ*、IGD和HV上的最优指标值分别提升了19.76%、89.07%和28.2%。
文摘Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures,received signal strength(RSS)-based indoor localization systems have received much attention.The placement of access points(APs)significantly influences localization accuracy and network access.However,the indoor scenario and network access are not fully considered in previous AP placement optimization methods.This study proposes a practical scenario modelingaided AP placement optimization method for improving localization accuracy and network access.In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods,we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method.After that,the localization and network access metrics are implemented in the multiple objective particle swarm optimization(MOPSO)solution,Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement.Finally,field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model.A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.
基金financially supported by Major scientific and Technological Innovation Projects of Shan Dong Province(Grant No.2019JZZY010728-01)supported by Bintuan Science and Technology Program(Grant No.2022DB001)Innovative Platform of Intelligent Agricultural Equipment Design and Manufacturing(Grant No.2021XDRHXMPT29).
文摘Large high clearance self-propelled sprayers were widely used in field plant protection due to their high-efficiency operation capabilities.Influenced by the characteristics of field operations such as high power,heavy weight,high ground clearance,and fast operation speed,the comprehensive requirements for the ride comfort,handling stability and road friendliness of the sprayer were increasingly strong.At the present stage,the chassis structure of the high clearance selfpropelled sprayer that attaches great importance to the improvement of comprehensive performance still has the problems of severe bumps,weak handling performance and serious road damage in complex field environments.Therefore,this paper proposes an optimization design method for hydro-pneumatic suspension system of a high clearance self-propelled sprayer based on the improved MOPSO(Multi-Objective Particle Swarm Optimization)algorithm,covering the entire process of configuration design,parameter intelligent optimization,and system verification of the high clearance self-propelled sprayer chassis.Specifically,chassis structure of the hydro-pneumatic suspension suitable for the high clearance self-propelled sprayer was designed,and a design method combining the improved MOPSO algorithm based on time-varying fusion strategy and adaptive update with the parameter optimization of hydro-pneumatic suspension based on this algorithm was proposed,and finally the software simulation and bench performance verification were carried out.The results show that the optimized hydropneumatic suspension has excellent vibration reduction effect,and the body acceleration,suspension dynamic deflection and tire deflection were increased by 16.5%,9.9%and 0.9%respectively,compared with those before optimization.The comprehensive performance of the hydro-pneumatic suspension designed in this study is better than that of the traditional suspension.
