By Zvi Retchkiman Konigsberg (auth.), Ying Tan, Yuhui Shi, Zhen Ji (eds.)
This booklet and its significant other quantity, LNCS vols. 7331 and 7332, represent the complaints of the 3rd overseas convention on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The one hundred forty five revised complete papers awarded have been conscientiously reviewed and chosen from 247 submissions. The papers are prepared in 27 cohesive sections overlaying all significant subject matters of swarm intelligence examine and developments.
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In formualting the Adaptive PBIL algorithm, we have tried to use simple equations so as to keep the simplicity of the algorithm. To show the effectiveness of the Adaptive PBIL, the algorithm was applied to the problem of optimizing the parameters of a power system stabilizer (PSS). Simulation results show that the PSS designed based on the Adaptive PBIL performs better than those based on standard PBIL and the Conventional PSS (CPSS). 2 Overview of the Standard PBIL PBIL is a technique that combines aspects of Genetic Algorithms and simple competitive learning derived from Artificial Neural Networks , .
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Advances in Swarm Intelligence: Third International Conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 Proceedings, Part I by Zvi Retchkiman Konigsberg (auth.), Ying Tan, Yuhui Shi, Zhen Ji (eds.)