Multimodal function optimizations with multiple maximums and multiple minimums using an improved PSO algorithm

2017 ◽  
Vol 60 ◽  
pp. 60-72 ◽  
Author(s):  
Wei-Der Chang
Keyword(s):  
Pso Algorithm ◽  
Multimodal Function ◽  
Improved Pso

scholarly journals Sliding Mode Control of Discrete Chaotic System Based on Multimodal Function Series Coupling

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Fengjun Hu
Keyword(s):  
Sliding Mode Control ◽  
Chaotic Systems ◽  
Sliding Mode ◽  
Extreme Points ◽  
Pso Algorithm ◽  
Clonal Selection Algorithm ◽  
Function Series ◽  
Mode Control ◽  
Multimodal Function ◽  
Improved Pso

A new sliding mode control model of discrete chaotic systems based on multimodal function series coupling is proposed to overcome the shortcomings of the standard PSO algorithm in multimodal function optimization. Firstly, a series coupled PSO algorithm (PP algorithm) based on multimodal function is constructed, which is optimized by multipeak solution on the basis of the standard PSO algorithm. Secondly, the improved PSO algorithm is applied to search all the extreme points in the feasible domain. Thirdly, the Powell method is used to perform the local optimization of the search results, and the newly generated extreme points are added to the extreme point database according to the same peak judgment operator. Finally, the long training time of PP algorithm can be overcome by the characteristics of fast convergence rate of the cloud mutation model. And also, both the population size and the redundancy can be reduced. Then, the clonal selection algorithm is used to keep the diversity of the population effectively. Simulation results of the sliding mode control of discrete chaotic systems show that the improved PSO algorithm obviously improves the response speed, overshoot, and so on.

Research on Improved PSO Algorithm Based on Contour Detection

2014 ◽  
Vol 644-650 ◽  
pp. 903-907
Author(s):  
Dan Li
Keyword(s):  
Pso Algorithm ◽  
Contour Detection ◽  
Noise Robustness ◽  
Snake Model ◽  
Detection Algorithms ◽  
Fitness Value ◽  
Multimodal Function ◽  
Non Linear ◽  
Improved Pso

In this paper, an improved PSO algorithm in unimodal, multimodal function can adapt quickly converges to a smaller fitness value. It’s suitable for complex non-linear environment. Combined with the adjusted Snake model can better convergence at the edge of the recess. Compared with other contour detection algorithms, this algorithm has better noise robustness, contour convergence accurate and efficient accuracy and efficiency.

Knowledge acquisition based on improved PSO algorithm and entropy

2009 ◽  
Vol 29 (8) ◽  
pp. 2245-2249 ◽  
Author(s):  
Xiang XU ◽  
Dong-bo ZHANG ◽  
Hui-xian HUANG ◽  
Zi-wen LIU
Keyword(s):  
Knowledge Acquisition ◽  
Pso Algorithm ◽  
Improved Pso

Improved PSO algorithm based on cosine functions and its simulation

2013 ◽  
Vol 33 (2) ◽  
pp. 319-322
Author(s):  
Min ZHANG ◽  
Qiang HUANG ◽  
Zhouzhao XU ◽  
Baizhuang JIANG
Keyword(s):  
Pso Algorithm ◽  
Cosine Functions ◽  
Improved Pso

An IES Comprehensive Profit Model Based On Improved PSO Algorithm

2019 ◽  
Author(s):  
Chen Chen ◽  
Bingjie Li ◽  
Wei Zhang ◽  
Hongda Zhao ◽  
Ciwei Gao ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Profit Model ◽  
Model Based ◽  
Improved Pso

scholarly journals Industrial robot trajectory planning based on improved pso algorithm

2021 ◽  
Vol 1820 (1) ◽  
pp. 012185
Author(s):  
Shunjie Han ◽  
Xinchao Shan ◽  
Jinxin Fu ◽  
Weijin Xu ◽  
Hongyan Mi
Keyword(s):  
Trajectory Planning ◽  
Industrial Robot ◽  
Pso Algorithm ◽  
Robot Trajectory ◽  
Improved Pso ◽  
Robot Trajectory Planning
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