找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Advanced Optimization by Nature-Inspired Algorithms; Omid Bozorg-Haddad Book 2018 Springer Nature Singapore Pte Ltd. 2018 Pattern Search (

[复制链接]
楼主: JAR
发表于 2025-3-26 23:36:07 | 显示全部楼层
发表于 2025-3-27 04:56:17 | 显示全部楼层
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.
发表于 2025-3-27 06:00:37 | 显示全部楼层
发表于 2025-3-27 12:35:49 | 显示全部楼层
发表于 2025-3-27 16:10:12 | 显示全部楼层
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
发表于 2025-3-27 21:16:44 | 显示全部楼层
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.
发表于 2025-3-28 00:07:09 | 显示全部楼层
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.
发表于 2025-3-28 03:48:20 | 显示全部楼层
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.
发表于 2025-3-28 10:10:49 | 显示全部楼层
发表于 2025-3-28 10:29:50 | 显示全部楼层
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.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-14 21:24
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表