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Titlebook: Engineering Applications of Modern Metaheuristics; Taymaz Akan,Ahmed M. Anter,Diego Oliva Book 2023 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-21 16:06:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Engineering Applications of Modern Metaheuristics
編輯Taymaz Akan,Ahmed M. Anter,Diego Oliva
視頻videohttp://file.papertrans.cn/311/310703/310703.mp4
概述Provides the reader with the most representative optimization tools used for scientific and engineering problems.Explains the algorithms used, the selected problem, and the implementation.Provides pra
叢書(shū)名稱Studies in Computational Intelligence
圖書(shū)封面Titlebook: Engineering Applications of Modern Metaheuristics; Taymaz Akan,Ahmed M. Anter,Diego Oliva Book 2023 The Editor(s) (if applicable) and The
描述.This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities..
出版日期Book 2023
關(guān)鍵詞Computational Intelligence; Metaheuristics; Optimization Algorithms; Swarm intelligence; Evolutionary al
版次1
doihttps://doi.org/10.1007/978-3-031-16832-1
isbn_softcover978-3-031-16834-5
isbn_ebook978-3-031-16832-1Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Metaheuristic Algorithms in IoT: Optimized Edge Node Localization,proposed hybrid metaheuristic algorithm tries to find the near-optimal solution with high efficiency by using the advantage of both algorithms. At the same time, the shortcomings of each will be eliminated. The proposed algorithm is used to solve the edge computing node localization problem, which i
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Minimum Transmission Power Control for the Internet of Things with Swarm Intelligence Algorithms,oaches are required for more efficient Internet of Things (IoT) usage. Wireless sensor networks (WSNs) contain energy-limited devices and calculating the minimum transmission power control (TPC) is a tackling process. Swarm intelligence is a subsection of AI and in the last four decades, many swarm
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A Meta-Heuristic Algorithm Based on the Happiness Model,imization algorithm called the happiness optimizer (HPO) algorithm. An HPO algorithm is designed based on personal behavior and demonstrated in 30 and 100 dimensions on benchmark functions. The model includes four questions: “what do you want?”, “what do you have?”, “what do others have?”, and “what
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Fitting Curves of Ruminal Degradation Using a Metaheuristic Approach,is inevitable to pay attention to all the needs and nutrient degradability and degradation fraction. This study aimed to investigate the use of particle swarm optimization (PSO) to describe the disappearance curves of . cuts. This paper uses the first-order kinetic model to describe the disappearanc
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Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques,re assigned to workstations aiming to minimize the required number of workstations, subject to considering a given production rate and satisfying the precedence relationships between tasks. Besides, line efficiency and smoothness index are considered as the second and the third objectives to select
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