Particle Swarm Optimization (PSO) | 私立大學五星教授網

In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate ...

粒子群最佳化（Particle Swarm Optimization, PSO），又稱粒子群演算法、微粒群演算法，是由J. Kennedy 和R. C. Eberhart 等於1995年開發的一種演化計算技術，來源於對 ...

2021年1月23日 — 本篇文章會以Python實作粒子群演算法。在啟發式演算法中，粒子群演算法是經典且相對容易實現的演算法，因此適合對啟發式演算法有興趣的讀者參閱。

2021年10月12日 — Particle swarm optimization (PSO) is one of the bio-inspired algorithms and it is a simple one to search for an optimal solution in the ...

2021年4月6日 — [最佳化演算法]粒子群演算法Particle swarm optimization (PSO) · Sign up to discover human stories that deepen your understanding of the world.

由 J Kennedy 著作 · 1995 · 被引用 83043 次 — A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, ...

由 AG Gad 著作 · 2022 · 被引用 264 次 — The idea is that, along appropriate directions, the prospect of generating new particles is maximized. Due to the lack of a priori knowledge of ...

The PSO algorithm is a powerful method to determine the optimum value of a complex function. It works based on particle movement and determines the best path ...

2023年5月25日 — Particle Swarm Optimization (PSO) is a powerful meta-heuristic optimization algorithm and inspired by swarm behavior observed in nature such as ...