A PSO-Based Bacterial Chemotaxis Algorithm and Its Application

被引：0

作者：

Zhang, Rui ^{[1
]}

Zhou, Jianzhong ^{[1
]}

Lu, Youlin ^{[1
]}

Qin, Hui ^{[1
]}

Zhang, Huifeng ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Coll Hydorpower Informat Engn, Wuhan 430074, Hubei, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT III | 2011年 / 6677卷

关键词：

bacterial chemotaxis algorithm; particle swarm operation; optimal operation; cascade hydropower station;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new two-phased optimization algorithm called BC-PSO is presented. Bacterial Chemotaxis Algorithm is a biologically inspired optimization method which is analyzing the way bacteria react to chemoattractants in concentration gradients. Aiming at the shortcomings of BC which is lack of global searching ability with low speed, PSO is introduced to accelerate convergence before BC works. With some famous test functions been used, the numerical experiment results and comparative analysis prove that it outperforms standard PSO and GA. Finally, the hybrid algorithm is applied to solve the problem of mid-long term optimal operation of cascade hydropower stations. Comparing with the other algorithms, the operation strategy shows its higher efficiency.

引用

页码：219 / 227

页数：9

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