Metaheuristic Algorithms: Theory and Practice
暫譯: 元啟發式演算法：理論與實務

Wang, Gai-Ge, Zhao, Xiaoqi, Li, Keqin

Metaheuristic Algorithms: Theory and Practice
  • 出版商: CRC
  • 出版日期: 2026-05-21
  • 售價: $2,520
  • 貴賓價: 9.5 折 $2,394
  • 語言: 英文
  • 頁數: 452
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032727608
  • ISBN-13: 9781032727608
  • 相關分類: Machine Learning

    • 海外代購書籍(需單獨結帳)

商品描述

This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans.

In the theoretical section, the book introduces the information feedback model, learning-based intelligent optimization, dynamic multi-objective optimization, and multi-model optimization. In the applications section, the book presents applications of optimization algorithms to neural architecture search, fuzz testing, oceans, and image processing. The neural architecture search chapter introduces the latest NAS method. The fuzz testing chapter uses multi-objective optimization and ant colony optimization to solve the seed selection and energy allocation problems in fuzz testing. In the ocean chapter, deep learning methods such as CNN, transformer, and attention-based methods are used to describe ENSO prediction and image processing for marine fish identification, and to provide an overview of traditional classification methods and deep learning methods.

Rich in examples, this book will be a great resource for students, scholars, and those interested in metaheuristic algorithms, as well as professional practitioners and researchers working on related topics.

商品描述(中文翻譯)

本書介紹了元啟發式演算法的理論與應用。它還提供了解決軟體工程、影像識別、視頻網絡及海洋等領域實際問題的方法。

在理論部分，本書介紹了資訊反饋模型、基於學習的智能優化、動態多目標優化以及多模型優化。在應用部分，本書展示了優化演算法在神經架構搜尋、模糊測試、海洋及影像處理中的應用。神經架構搜尋章節介紹了最新的 NAS 方法。模糊測試章節利用多目標優化和蟻群優化來解決模糊測試中的種子選擇和能量分配問題。在海洋章節中，使用深度學習方法如 CNN、transformer 和基於注意力的方法來描述 ENSO 預測及海洋魚類識別的影像處理，並提供傳統分類方法和深度學習方法的概述。

本書範例豐富，將成為學生、學者及對元啟發式演算法感興趣的讀者，以及從事相關主題的專業實務者和研究人員的重要資源。

作者簡介

Gai-Ge Wang is currently a Professor with the Ocean University of China, Qingdao, China. His entire published works have been cited more 15,000 times (Google Scholar). The latest Google H-index and i10-index are 62 and 131, respectively. Of his 81 Highly Cited Papers, 15 were selected by Web of Science and 66 selected by Scopus. His research interests include swarm intelligence, evolutionary computation, and big data optimization.

Xiaoqi Zhao is currently working at Qingdao University of Technology, China. She graduated from Ocean University of China with a PhD degree and her main research interests are information security, fuzz testing and intelligent optimization.

Keqin Li is a SUNY Distinguished Professor (USA) and a National Distinguished Professor (China). He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the American Association for the Advancement of Science (AAAS), and a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA). He is a Member of Academia Europaea (Academician of the Academy of Europe).

作者簡介(中文翻譯)

王改革目前是中國青島海洋大學的教授。他的所有出版作品已被引用超過15,000次（Google Scholar）。最新的Google H指數和i10指數分別為62和131。在他的81篇高被引論文中，有15篇被Web of Science選中，66篇被Scopus選中。他的研究興趣包括群體智慧、演化計算和大數據優化。

趙小琪目前在中國青島科技大學工作。她畢業於中國海洋大學，獲得博士學位，主要研究興趣為資訊安全、模糊測試和智能優化。

李克勤是美國紐約州立大學的傑出教授（SUNY Distinguished Professor）及中國的國家傑出教授。他是電氣和電子工程師學會（IEEE）的會士、美國科學促進會（AAAS）的會士，以及亞太人工智慧協會（AAIA）的會士。他是歐洲科學院的成員（Academia Europaea）。

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