Computational Intelligence Applied to Inverse Problems in Radiative Transfer - Brossura

9783031435461: Computational Intelligence Applied to Inverse Problems in Radiative Transfer

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ISBN 10: 303143546X ISBN 13: 9783031435461

Casa editrice: Springer, 2024

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EditoreSpringer
Data di pubblicazione2024
ISBN 10 303143546X
ISBN 13 9783031435461
RilegaturaCopertina flessibile
LinguaInglese
Numero di pagine268
RedattoreSilva Neto Ant�nio Jos� Da, Becceneri Jos� Carlos, Campos Velho Haroldo Fraga De

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Computational Intelligence Applied to Inverse Problems in Radiative Transfer

Ant�nio Jos� Da Silva Neto

Editore: Springer International Publishing, Springer Nature Switzerland Dez 2024, 2024

ISBN 10: 303143546X ISBN 13: 9783031435461

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 268 pp. Englisch. Codice articolo 9783031435461

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Computational Intelligence Applied to Inverse Problems in Radiative Transfer

Ant�nio Jos� Da Silva Neto

Editore: Springer International Publishing, Springer Nature Switzerland, 2024

ISBN 10: 303143546X ISBN 13: 9783031435461

Nuovo Taschenbuch

Da: AHA-BUCH GmbH, Einbeck, Germania

Valutazione del venditore 5 su 5 stelle

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783031435461

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