By Tim Landgraf, Hai Nguyen, Stefan Forgo, Jan Schneider, Joseph Schröer, Christoph Krüger (auth.), Ying Tan, Yuhui Shi, Hongwei Mo (eds.)
This e-book and its better half quantity, LNCS vols. 7928 and 7929 represent the lawsuits of the 4th foreign convention on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised complete papers provided have been rigorously reviewed and chosen from 268 submissions. The papers are equipped in 22 cohesive sections overlaying all significant themes of swarm intelligence learn and advancements. the next subject matters are coated during this quantity: research of swarm intelligence dependent algorithms, particle swarm optimization, purposes of particle swarm optimization algorithms, ant colony optimization algorithms, biogeography-based optimization algorithms, novel swarm-based seek tools, bee colony algorithms, differential evolution, neural networks, fuzzy tools, evolutionary programming and evolutionary games.
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Additional info for Advances in Swarm Intelligence: 4th International Conference, ICSI 2013, Harbin, China, June 12-15, 2013, Proceedings, Part I
The vertical axis is the common log of the average extremum and the horizontal axis is corresponding iterations. To avoid function value being zero, 10-11 was added to each value as the final values. It can be seen from the illustrations that the best average optimization result of all functions is gained when the algorithm is without GO (S3), while the worst is gained when the algorithm is without RO (S4). In general, the order of the average optimization result of all control strategies from high to low is: S3, S2, S1, S4.
5) can transfer sequence number of firework rank of fitness to different value of function, which is used to calculate the spark number and amplitude of firework explosion. (5) is named as transfer function. 3 which x axis denotes sequence number. 3, it can be found that the function fitness of different sequence number is more and more mean as the parameter a is increasing. So, the calculating number of explosion sparks is designed as the following equation: f (n) (6) Sn = m N f (n) n=1 Where m is the total of number of spark, n is the sequence number of a firework.
The p(xi ) is the probability which the ith firework or spark is selected as the firework of next generation. (11) do not consider the fitness of sparks 18 J. Liu, S. Zheng, and Y. Tan or fireworks for the selection of next generation fireworks’ location. (7). (11) of original FWA don’t consider the fitness to select the firework location. Therefore, there are two methods to be provided to modify the selection operator. 1. Fitness Selection using the roulette Like the original FWA, the best of the set will be selected first.