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Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm 认领 引用 被引量：1
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作者 姜文英 林焰 +1 位作者 陈明 于雁云 《Journal of Shanghai Jiaotong university(Science)》 EI 2015年第5期565-570,共6页
Based on the improved particle swarm optimization(PSO) algorithm,an optimization approach for the cargo oil tank design(COTD) is presented in this paper.The purpose is to design an optimal overall dimension of the car... Based on the improved particle swarm optimization(PSO) algorithm,an optimization approach for the cargo oil tank design(COTD) is presented in this paper.The purpose is to design an optimal overall dimension of the cargo oil tank(COT) under various kinds of constraints in the preliminary design stage.A non-linear programming model is built to simulate the optimization design,in which the requirements and rules for COTD are used as the constraints.Considering the distance between the inner shell and hull,a fuzzy constraint is used to express the feasibility degree of the double-hull configuration.In terms of the characteristic of COTD,the PSO algorithm is improved to solve this problem.A bivariate extremum strategy is presented to deal with the fuzzy constraint,by which the maximum and minimum cargo capacities are obtained simultaneously.Finally,the simulation demonstrates the feasibility and effectiveness of the proposed approach. 展开更多
关键词 cargo oil tank optimization design nonlinear programming improved particle swarm optimization（PSO）algorithm fuzzy constraint construction feasibility degree
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Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor 认领 引用 被引量：2
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作者 Shuai Zhou Dazhi Wang +2 位作者 Yongliang Ni Keling Song Yanming Li 《Computers, Materials & Continua》 SCIE EI 2024年第5期2187-2207,共21页
In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parame... In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness. 展开更多
关键词 Transformation function filled function fuzzy particle swarm optimization algorithm permanent magnet synchronous motor parameter identification
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Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm 认领 引用 被引量：16
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作者 PEI JiaZheng SU YiXin ZHANG DanHong 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2017年第3期425-433,共9页
Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybri... Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em- 展开更多
关键词 parallel hybrid electric vehicles（parallel HEV） energy management strategy（EMS） fuzzy controller pigeon-inspired optimization（PIO） algorithm quantum evolution chaotic search
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