Analytical and empirical study of particle swarm optimization with a sigmoid decreasing inertia weight
The particle swarm optimization (PSO) is an algorithm for finding optimal regions of complex search space through interaction of individuals in a population of particles. Search is conducted by moving particles in the space. Some methods area attempted to improve performance of PSO since is founded,...
Saved in:
Main Authors: | Adriansyah, Andi, H. M. Amin, Shamsudin |
---|---|
格式: | Article |
語言: | English |
出版: |
School of Postgraduate Studies, UTM
2006
|
主題: | |
在線閱讀: | http://eprints.utm.my/id/eprint/1690/1/sham06_Analytical_study.pdf http://eprints.utm.my/id/eprint/1690/ |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
New particle swarm optimizer with sigmoid increasing inertia weight
由: Malik , Reza Firsandaya, et al.
出版: (2007) -
Analysis of vector evaluated particle swarm optimization guided by non-dominated solutions: Inertia weight, cognitive, and social constants
由: Lim, K. S., et al.
出版: (2015) -
Analysis of Vector Evaluated Particle Swarm Optimization Guided by Non-Dominated Solutions : Inertia Weight, Cognitive, and Social Constants
由: Kian, Sheng Lim, et al.
出版: (2014) -
A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
由: Too, Jing Wei, et al.
出版: (2019) -
Particle swarm fuzzy controller for behavior - based mobile robot
由: Adriansyah, Andi
出版: (2007)