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商品描述
The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.
商品描述(中文翻譯)
本書的目的是了解群體智慧的最先進理論和實踐進展。內容包括七個當代相關的章節。在第一章中，介紹了細菌覓食優化（Bacteria Foraging Optimization, BFO）技術，針對單一和多重標準問題進行回顧。第二章提供了針對多重和多目標優化的群體智慧調查，並進行了腦電圖（EEG）信號分析的主題研究。在不妥協於廣泛模擬研究的情況下，第三章提供了多目標粒子群優化（MOPSO）變體的比較研究。第四章和第七章討論了不同的混合群體智慧技術所面臨的難以處理的問題，如子集問題和作業排程問題。第五章嘗試通過螞蟻群優化進行圖像增強的研究。最後，第七章涵蓋了混合粒子群優化（PSO）在數據不確定性方面的應用。
