| 書(shū)目名稱(chēng) | Computational Intelligence Applied to Inverse Problems in Radiative Transfer | | 編輯 | Ant?nio José da Silva Neto,José Carlos Becceneri,H | | 視頻video | http://file.papertrans.cn/233/232379/232379.mp4 | | 概述 | Provides an impressive selection of computational intelligence techniques, focusing on biologically inspired methods.Presents inverse problems in radiative transfer as optimization problems which can | | 圖書(shū)封面 |  | | 描述 | This book offers a careful selection of studies in optimization techniques based on artificial intelligence, applied to inverse problems in radiative transfer.?In this book, the reader will find an in-depth exploration of heuristic optimization methods, each meticulously described and accompanied by historical context and natural process analogies..From simulated annealing and genetic algorithms to artificial neural networks, ant colony optimization, and particle swarms, this volume presents a wide range of heuristic methods. Additional approaches such as generalized extreme optimization, particle collision, differential evolution, Luus-Jaakola, and firefly algorithms are also discussed, providing a rich repertoire of tools for tackling challenging problems..While the applications showcased primarily focus on radiative transfer, their potential extends to various domains, particularly nonlinear and large-scale problems where traditional deterministic methods fall short. With clear and comprehensive presentations, this book empowers readers to adapt each method to their specific needs. Furthermore, practical examples of classical optimization problems and application suggestions are | | 出版日期 | Book 2023 | | 關(guān)鍵詞 | computational intellilgence; inverse problems; optimization; radiation; differential equations; artificia | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-43544-7 | | isbn_softcover | 978-3-031-43546-1 | | isbn_ebook | 978-3-031-43544-7 | | copyright | Springer Nature Switzerland AG 2023 |
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