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Titlebook: Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering; Gustavo Mendes Platt,Xin-She Yang,Antônio

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发表于 2025-3-21 18:10:45 | 显示全部楼层 |阅读模式
书目名称Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering
编辑Gustavo Mendes Platt,Xin-She Yang,Antônio José Sil
视频videohttp://file.papertrans.cn/233/232556/232556.mp4
概述Highlights a wealth of applications of metaheuristics to real-world problems from several areas of Engineering.Describes improved versions of classical metaheuristic methods, such as Bat Algorithms an
图书封面Titlebook: Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering;  Gustavo Mendes Platt,Xin-She Yang,Antônio
描述This book focuses on metaheuristic methods and its applications to real-world problems in Engineering. The first part describes some key metaheuristic methods, such as Bat Algorithms, Particle Swarm Optimization, Differential Evolution, and Particle Collision Algorithms. Improved versions of these methods and strategies for parameter tuning are also presented, both of which are essential for the practical use of these important computational tools. The second part then applies metaheuristics to problems, mainly in Civil, Mechanical, Chemical, Electrical, and Nuclear Engineering. Other methods, such as the Flower Pollination Algorithm, Symbiotic Organisms Search, Cross-Entropy Algorithm, Artificial Bee Colonies, Population-Based Incremental Learning, Cuckoo Search, and Genetic Algorithms, are also presented. The book is rounded out by recently developed strategies, or hybrid improved versions of existing methods, such as the Lightning Optimization Algorithm, Differential Evolution with Particle Collisions, and Ant Colony Optimization with Dispersion – state-of-the-art approaches for the application of computational intelligence to engineering problems..The wide variety of methods an
出版日期Book 2019
关键词computational intelligence; metaheuristics; evolutionary algorithms; bioinspired algorithms; nature-insp
版次1
doihttps://doi.org/10.1007/978-3-319-96433-1
isbn_softcover978-3-030-07190-5
isbn_ebook978-3-319-96433-1
copyrightSpringer Nature Switzerland AG 2019
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发表于 2025-3-21 23:08:17 | 显示全部楼层
Reliability-Based Robust Optimization Applied to Engineering System Design,e of errors, i.e., without the influence of uncertainties). However, small variations in these quantities can affect the considered objective functions and, consequently, the resulting design of the system. Probabilistic methods have been proposed to deal with this kind of problem. These methodologi
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On Initial Populations of Differential Evolution for Practical Optimization Problems,on: the selection of an initial population of solutions. We use differential evolution to test two different generation schemes besides pseudorandom generation: random generation followed by the application of opposition-based learning, and the Sobol quasi-random generator. So far, to the best of ou
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,Rotation-Based Multi-Particle Collision Algorithm with Hooke–Jeeves Approach Applied to the Structuage. A new version of the MPCA is formulated with the rotation-based learning mechanism to the exploration search. The inverse problem of damage identification is formulated as an optimization problem assuming the displacement time history as experimental data. The objective function is the square d
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A Bioreactor Fault Diagnosis Based on Metaheuristics,e, depend on the correct diagnosis of systems. Robustness in relation to external disturbances, which may affect the system, sensible to incipient faults, and a proper diagnosis time are desired characteristics of the diagnosis, in order to prevent propagation of faults. In the particular case of th
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Inverse Problem of an Anomalous Diffusion Model Employing Lightning Optimization Algorithm,e cases this approach does not represent the actual physical behavior. In most published works dealing with this situation, the well-known second-order parabolic equation is assumed to be the basic equation of the dispersion process, but the anomalous diffusion effect is modeled with the introductio
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