Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications
暫譯: 蛾火優化演算法手冊：變體、混合、改進與應用

Mirjalili, Seyedali

Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications
  • 出版商: CRC
  • 出版日期: 2022-09-20
  • 售價: $4,510
  • 貴賓價: 9.5 折 $4,285
  • 語言: 英文
  • 頁數: 332
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032070919
  • ISBN-13: 9781032070919
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

商品描述

Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.

Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.

Key Features:

  • Reviews the literature of the Moth-Flame Optimization algorithm
  • Provides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithm
  • Proposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems
  • Demonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithm
  • Introduces several applications areas of the Moth-Flame Optimization algorithm

This handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas.

商品描述(中文翻譯)

《蛾火優化演算法手冊：變體、混合、改進與應用》提供了對這種演算法的深入分析，以及文獻中現有的方法來應對這些挑戰。

蛾火優化演算法是一種新興的元啟發式演算法，已廣泛應用於科學和工業中。使用此演算法解決優化問題需要面對多個挑戰，包括多目標、約束條件、二元決策變數、大規模搜尋空間、動態目標函數和噪聲參數。

主要特點：
- 回顧蛾火優化演算法的文獻
- 提供蛾火優化演算法的方程式、數學模型和機制的深入分析
- 提出不同的蛾火優化演算法變體，以解決二元、多目標、噪聲、動態和組合優化問題
- 演示如何設計、開發和測試不同的蛾火優化演算法混合體
- 介紹蛾火優化演算法的幾個應用領域

本手冊將吸引對進化計算和元啟發式演算法感興趣的研究人員，以及那些有興趣將蛾火優化演算法和群體智慧方法應用於不同應用領域的人士。

作者簡介

Seyedali Mirjalili is a Professor at Torrens University Center for Artificial Intelligence Research and Optimization and internationally recognized for his advances in nature-inspired Artificial Intelligence (AI) techniques. He is the author of more than 300 publications including five books, 250 journal articles, 20 conference papers, and 30 book chapters. With more than 50,000 citations and H-index of 75, he is one of the most influential AI researchers in the world. From Google Scholar metrics, he is globally the most cited researcher in Optimization using AI techniques, which is his main area of expertise. Since 2019, he has been in the list of 1% highly-cited researchers and named as one of the most influential researchers in the world by Web of Science. In 2021, The Australian newspaper named him as the top researcher in Australia in three fields of Artificial Intelligence, Evolutionary Computation, and Fuzzy Systems. He is a senior member of IEEE and is serving as an editor of leading AI journals including Neurocomputing, Applied Soft Computing, Advances in Engineering Software, Computers in Biology and Medicine, Healthcare Analytics, and Applied Intelligence.

作者簡介(中文翻譯)

Seyedali Mirjalili 是托倫斯大學人工智慧研究與優化中心的教授，因其在自然啟發的人工智慧 (AI) 技術方面的進展而享有國際聲譽。他擁有超過 300 篇出版物，包括五本書籍、250 篇期刊文章、20 篇會議論文和 30 篇書章。擁有超過 50,000 次引用和 75 的 H 指數，他是全球最具影響力的 AI 研究者之一。根據 Google Scholar 的指標，他是全球在使用 AI 技術進行優化方面被引用最多的研究者，這也是他的主要專業領域。自 2019 年以來，他一直名列 1% 高被引用研究者名單，並被 Web of Science 評選為全球最具影響力的研究者之一。在 2021 年，《澳大利亞人報》將他評選為澳大利亞在人工智慧、進化計算和模糊系統三個領域的頂尖研究者。他是 IEEE 的高級會員，並擔任多本領先 AI 期刊的編輯，包括 Neurocomputing、Applied Soft Computing、Advances in Engineering Software、Computers in Biology and Medicine、Healthcare Analytics 和 Applied Intelligence。

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