Computational Intelligence Applied To Inverse Problems In Radiative Transfer
Download Computational Intelligence Applied To Inverse Problems In Radiative Transfer PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Computational Intelligence Applied To Inverse Problems In Radiative Transfer book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Computational Intelligence Applied to Inverse Problems in Radiative Transfer
Author: Antônio José da Silva Neto
language: en
Publisher: Springer Nature
Release Date: 2023-12-12
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.
Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering
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 and applications, as well as the original results to problems of practical engineering interest, represent the primary differentiation and distinctive quality of this book. Furthermore, it gathers contributions by authors from four countries – some of which are the original proponents of the methods presented – and 18 research centers around the globe.
Computational Intelligence Methodologies Applied to Sustainable Development Goals
Author: José Luis Verdegay
language: en
Publisher: Springer Nature
Release Date: 2022-04-15
This book presents computational intelligence methodologies and its applications to sustainable development goals. Along 18 chapters prepared by reputed scientists around the world, this book explores and focuses on the impacts produced by the application of artificial intelligence and mainly of computational intelligence, in sustainable development goals and on analysing how particularly computational intelligence can influence the ability to comply in a timely manner with all the sustainable development goals. Specialists from STEM areas will find in this book an attractive showcase of instances and research lines to be explored.