Computational Intelligence Applied to Inverse Problems in Radiative Transfer

Computational Intelligence Applied to Inverse Problems in Radiative Transfer
Author :
Publisher : Springer Nature
Total Pages : 258
Release :
ISBN-10 : 9783031435447
ISBN-13 : 3031435443
Rating : 4/5 (47 Downloads)

Book Synopsis Computational Intelligence Applied to Inverse Problems in Radiative Transfer by : Antônio José da Silva Neto

Download or read book Computational Intelligence Applied to Inverse Problems in Radiative Transfer written by Antônio José da Silva Neto and published by Springer Nature. This book was released on 2024-01-13 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 included to enhance your understanding. This book is suitable to any researcher or practitioner whose interests lie on optimization techniques based in artificial intelligence and bio-inspired algorithms, in fields like Applied Mathematics, Engineering, Computing, and cross-disciplinary areas.


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