繁荣地区
发表于 2025-3-26 23:36:07
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真繁荣
发表于 2025-3-27 04:56:17
Giuseppe Pignatti,Sandro Pignatti eggs. The basis of the algorithm is made by the attempt to survive. While competing for being survived, some of them are demised. The survived cuckoos immigrate to better areas and start reproducing and laying eggs. Finally, the survived cuckoos are converged in a way that there is a cuckoo society with the same profit rate.
顶点
发表于 2025-3-27 06:00:37
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bisphosphonate
发表于 2025-3-27 12:35:49
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删减
发表于 2025-3-27 16:10:12
Book 2018s been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications
LVAD360
发表于 2025-3-27 21:16:44
https://doi.org/10.1007/978-981-16-9777-7This chapter briefly describes the league championship algorithm (LCA) as one of the new evolutionary algorithms. In this chapter, a brief literature review of LCA is first presented; and then the procedure of holding a common league in sports and its rules are described. Finally, a pseudo code of LCA is presented.
Intellectual
发表于 2025-3-28 00:07:09
The Importance of Marine Biodiversity,This chapter is designed to describe the flower pollination algorithm (FPA) which is a new metaheuristic algorithm. First, the FPA applications in different problems are summarized. Then, the natural pollination process and the flower pollination algorithm are described. Finally, a pseudocode of the FPA is presented.
安定
发表于 2025-3-28 03:48:20
Stephen P. Kirkman,Kumbi Kilongo NsingiThis chapter describes the grey wolf optimization (GWO) algorithm as one of the new meta-heuristic algorithms. First, a brief literature review is presented and then the natural process of the GWO algorithm is described. Also, the optimization process and a pseudo code of the GWO algorithm are presented in this chapter.
Mercurial
发表于 2025-3-28 10:10:49
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规范就好
发表于 2025-3-28 10:29:50
The Freshwater Fishes of AngolaThis chapter introduces the Moth-Flame Optimization (MFO) algorithm, along with its applications and variations. The basic steps of the algorithm are explained in detail and a flowchart is represented. In order to better understand the algorithm, a pseudocode of the MFO is also included.