adaptiveparticleswarmoptimization

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented.

由 ZH Zhan 著作 · 2009 · 被引用 2281 次 — Abstract: An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization ...

由 ZH Zhan 著作 · 2009 · 被引用 2284 次 — The. PSO uses a simple mechanism that mimics swarm behavior in birds flocking and fish schooling to guide the particles to search for globally optimal solutions ...

由 W Yue 著作 · 2022 · 被引用 1 次 — This paper presents an optimal design method to solve the initial optical parameters, which is used for the common-aperture design including transmission ...

由 W Li 著作 · 2021 · 被引用 9 次 — Abstract. Particle swarm optimization (PSO) algorithm has some advantages, such as fewer control parameters, and faster convergence speed.

由 F Jiang 著作 · 2019 · 被引用 9 次 — As a clustering intelligence algorithm, the PSO algorithm simulates the behaviour of bird flock foraging, and achieves the goal of optimization ...

由 F Qian 著作 · 2020 · 被引用 6 次 — This theory is used to move the swarms with high spatial distribution diversity to the global optimum and also to move the swarms with low level of diversity to ...

由 C Walha 著作 · 2012 · 被引用 9 次 — This paper proposes an adaptive particle swarm optimization (APSO) approach to solve the grasp planning problem. Each particle represents a configuration ...

由 Z Su 著作 · 2022 — In this paper, we aim at the problem of rapid loss of population diversity encountered in the application of PSO algorithm. A feedback strategy is proposed ...