PSO algorithm convergence analysis based on time-invariant linear iterative method

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (31): 35-37.

• 研究、探讨 • Previous Articles Next Articles

PSO algorithm convergence analysis based on time-invariant linear iterative method

ZHANG Huibin，WANG Hongbin，HU Zhijun

Department of Computer Science and Technology，Xinzhou Teachers College，Xinzhou，Shanxi 034000，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-11-01 Published:2011-11-01

基于定常线性迭代法的PSO算法收敛性分析

张慧斌，王鸿斌，胡志军

忻州师范学院计算机科学与技术系，山西忻州 034000

Abstract

Abstract: The PSO algorithm itself is in the linear time-variable discrete system.The existing convergence study of PSO algorithm is conducted by transforming it into linear time-invariant discrete systems through certain supposition.The mathematical model of both linear time-invariant discrete system and solving single-step time-invariant linear iterative method of linear equations group is exactly the same.So stability analysis of linear time-invariant discrete systems can be transformed into convergence analysis of single-step time-invariant linear iterative method.In this way，a new way is obtained to think and solve on convergence analysis study of the PSO algorithm.

Key words: Particle Swarm Optimization（PSO） algorithm, linear time-varying discrete systems, linear time-invariant discrete systems, single-step time-invariant linear iterative method, convergence analysis

摘要： PSO算法本身是线性时变离散系统，现有的PSO算法收敛性条件的研究都是通过一定的假设将其转化为线性定常离散系统，线性定常离散系统的数学模型与求解线性方程组的单步定常线性迭代法的数学模型完全一致，这样对线性定常离散系统的稳定性分析就转化为对单步定常线性迭代格式的收敛性分析，为PSO算法的收敛性研究提供了一种新的思路和方法。

关键词: PSO算法, 线性时变离散系统, 线性定常离散系统, 单步定常线性迭代格式, 收敛性分析

ZHANG Huibin，WANG Hongbin，HU Zhijun. PSO algorithm convergence analysis based on time-invariant linear iterative method[J]. Computer Engineering and Applications, 2011, 47(31): 35-37.

张慧斌，王鸿斌，胡志军

. 基于定常线性迭代法的PSO算法收敛性分析[J]. 计算机工程与应用, 2011, 47(31): 35-37.

[1]	WANG Jiayue, SHI Li. Research on Path Optimization and Charging Strategy of Electric Refrigerated Vehicle Considering Cost of Battery Capacity Degradation [J]. Computer Engineering and Applications, 2021, 57(24): 283-289.
[2]	LIAO Weilin, CHENG Shan, SHANG Dongdong, WEI Zhaobin. Particle Swarm Optimization Algorithm Integrated with Multiple-Strategies [J]. Computer Engineering and Applications, 2021, 57(1): 69-76.
[3]	HONG Tianlong, XIE Lijun, HE Lisha, NI Zhongyi, ZHENG Yao. Auto Tunning for In-Situ Volume Depth Image Generation Based on Particle Swarm Optimization Algorithm [J]. Computer Engineering and Applications, 2019, 55(11): 237-243.
[4]	SHI Xianming, LIU Yi’an. Digital modulation recognition method based on MPSO optimizing BP neural network [J]. Computer Engineering and Applications, 2016, 52(17): 133-139.
[5]	YUAN Liqiao, YANG Xiwang, YANG Mengru. Research on QoS routing algorithm based on PSO classified by BP neural network [J]. Computer Engineering and Applications, 2015, 51(9): 98-102.
[6]	LI Rong, SHEN Yunbo, LIU Jian. Improved adaptive Particle Swarm Optimization algorithm [J]. Computer Engineering and Applications, 2015, 51(13): 31-36.
[7]	SHENG Xinyi1, SUN Jun2, ZHOU Di1, XU Wenbo2. Quantum-behaved particle swarm optimization method based on Q-learning [J]. Computer Engineering and Applications, 2014, 50(21): 8-13.
[8]	SHENG Xinyi1, SUN Jun2, ZHOU Di1, XU Wenbo2. Self-learning quantum-behaved particle swarm optimization algorithm [J]. Computer Engineering and Applications, 2014, 50(20): 24-29.
[9]	ZHAO Yu, SUN Ting. Wireless indoor location method based on PSO-SVM [J]. Computer Engineering and Applications, 2014, 50(19): 95-98.
[10]	LI Junwu, YU Zhifu. Improved PSO and its application to DOA estimation [J]. Computer Engineering and Applications, 2013, 49(9): 203-206.
[11]	GONG Guobin. Adaptive constrained optimization hybrid Particle Swarm Optimization algorithm [J]. Computer Engineering and Applications, 2013, 49(9): 50-53.
[12]	KAN Chaohao. Particle Swarm Optimization with comprehensive learning & self-adaptive [J]. Computer Engineering and Applications, 2013, 49(6): 23-28.
[13]	ZHANG Yu1, TONG Minming2, DAI Guiping1. CO concentration detection based on OBLPSO-LSSVM [J]. Computer Engineering and Applications, 2013, 49(24): 249-252.
[14]	SONG Cunli. Co-evolution Particle Swarm Optimization algorithm for flexible job-shop scheduling problem [J]. Computer Engineering and Applications, 2013, 49(21): 15-18.
[15]	SHI Hao, LAI Huicheng, QIN Xizhong. Image segmentation algorithm of cotton based on PSO and K-means hybrid clustering [J]. Computer Engineering and Applications, 2013, 49(21): 226-229.

PSO algorithm convergence analysis based on time-invariant linear iterative method

基于定常线性迭代法的PSO算法收敛性分析

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics