vitamin-D
发表于 2025-3-21 17:18:35
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注视
发表于 2025-3-21 22:15:14
Book 2016ave proved to be effective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO),3) the States of Matter
格言
发表于 2025-3-22 03:33:03
1860-949X fective in adapting a determined EC method to a specific pro.The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective in the solutionof several complex problems. The book has been st
低三下四之人
发表于 2025-3-22 05:34:01
An Evolutionary Computation Algorithm based on the Allostatic Optimization,t body conditions which interact to each other by using operators based on the biological principles of the allostasis mechanism. The proposed method has been compared to other well-known optimization algorithms. The results show good performance of the proposed method when searching for a global optimum of several benchmark functions.
大洪水
发表于 2025-3-22 12:35:44
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Eeg332
发表于 2025-3-22 13:26:17
Oleksiy Shulika,Igor Sukhoivanovhods. The comparison examines several standard benchmark functions which are commonly considered within the literature of evolutionary algorithms. The results and examples show a high performance of the presented method when searching for a global optimum of several benchmark functions.
headlong
发表于 2025-3-22 19:40:16
Comprehensive Rehabilitation of Oral Cancer,he biological laws of collective motion. The optimization method presented in this chapter has been compared to other well-known optimization algorithms. The results, experiments and practical examples confirm the high performance of the presented method to find a global optimum of several benchmark functions.
公司
发表于 2025-3-22 23:04:10
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neuron
发表于 2025-3-23 02:22:46
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delta-waves
发表于 2025-3-23 08:36:32
The Collective Animal Behavior method,he biological laws of collective motion. The optimization method presented in this chapter has been compared to other well-known optimization algorithms. The results, experiments and practical examples confirm the high performance of the presented method to find a global optimum of several benchmark functions.