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Titlebook: Glowworm Swarm Optimization; Theory, Algorithms, Krishnanand N. Kaipa,Debasish Ghose Book 2017 Springer International Publishing AG 2017 G

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樓主: Truman
21#
發(fā)表于 2025-3-25 04:58:39 | 只看該作者
22#
發(fā)表于 2025-3-25 07:30:09 | 只看該作者
GSO Applications and Extensions,vergence properties of original GSO or modifying GSO for global optimization problems. In the second category, researchers used basic GSO in different applications. In the third category, other researchers modified GSO and used them in some applications. Table?. summarizes this classification.
23#
發(fā)表于 2025-3-25 14:16:49 | 只看該作者
1860-949X ying ideas, theoretical foundations, algorithm development, This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basi
24#
發(fā)表于 2025-3-25 15:58:39 | 只看該作者
https://doi.org/10.1007/978-3-642-37326-8vergence properties of original GSO or modifying GSO for global optimization problems. In the second category, researchers used basic GSO in different applications. In the third category, other researchers modified GSO and used them in some applications. Table?. summarizes this classification.
25#
發(fā)表于 2025-3-25 22:01:44 | 只看該作者
26#
發(fā)表于 2025-3-26 01:05:05 | 只看該作者
Earll Murman,Thomas Allen,Sheila Widnallroduced, which is followed by a description of the phases that constitute each cycle of the algorithm. GSO, in its present form, has evolved out of several significant modifications incorporated into the earlier versions of the algorithm. Many ideas were considered in the development process before
27#
發(fā)表于 2025-3-26 05:40:43 | 只看該作者
Bootstrapping an Incubation Program,foundations for GSO. Initially, a characterization of the swarming behavior of agents in GSO is carried out, which guides the formulation of a framework used to analyze the algorithm. A theoretical model of GSO is obtained by using assumptions that make it amenable to analysis, yet reflecting most o
28#
發(fā)表于 2025-3-26 11:46:25 | 只看該作者
29#
發(fā)表于 2025-3-26 14:30:27 | 只看該作者
Claus Sehested,Henrik Sonnenbergrevious chapters. However, in this chapter, the behavior of GSO agents in the presence of mobile sources is investigated. In particular, a coordination scheme based on GSO is developed that enables a swarm of glowworms to pursue a group of mobile signal sources. Examples of such sources include host
30#
發(fā)表于 2025-3-26 19:10:26 | 只看該作者
https://doi.org/10.1007/978-3-642-37326-8assified into three categories. Researchers in the first category proposed modifications of GSO, which were mainly focused on either improving the convergence properties of original GSO or modifying GSO for global optimization problems. In the second category, researchers used basic GSO in different
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