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Computational Intelligence Applied to Inverse Problems in Radiative Transfer / edited by Antônio José da Silva Neto, José Carlos Becceneri, Haroldo Fraga de Campos Velho.

Springer Nature - Springer Mathematics and Statistics eBooks 2023 English International Available online

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Format:
Book
Author/Creator:
Silva Neto, Antônio José da.
Contributor:
Becceneri, José Carlos.
Campos Velho, Haroldo Fraga de.
Teixeira, Ricardo.
Language:
English
Subjects (All):
Mathematics--Data processing.
Mathematics.
Mathematical models.
Computational intelligence.
Mathematical optimization.
Computer science.
Computational Science and Engineering.
Mathematical Modeling and Industrial Mathematics.
Computational Intelligence.
Optimization.
Computer Science.
Local Subjects:
Computational Science and Engineering.
Mathematical Modeling and Industrial Mathematics.
Computational Intelligence.
Optimization.
Computer Science.
Physical Description:
1 online resource (258 pages)
Edition:
1st ed. 2023.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2023.
Summary:
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.
Contents:
Foreword
Preface
Introduction
Radiative Transfer
Inverse Problems in Radiative Transfer: An Implicit Formulation
Computational Intelligence in Optimization Problems
Simulated Annealing
Genetic Algorithms
Artificial Neural Networks
Ant Colony Optimization
Artificial Bee Colony Algorithm
Particle Swarm Optimization
Generalized Extremal Optimization
Particle Collision Algorithm
Differential Evolution
Luus-Jaakola Algorithm
Firefly Algorithm
Application Projects
Final Considerations
References.
ISBN:
9783031435447
3031435443
OCLC:
1414458133

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