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Metaheuristic Procedures For Training Neural Networks


Metaheuristic Procedures For Training Neural Networks
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Metaheuristic Procedures For Training Neural Networks


Metaheuristic Procedures For Training Neural Networks
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Author : Enrique Alba
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-25

Metaheuristic Procedures For Training Neural Networks written by Enrique Alba and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-25 with Business & Economics categories.


Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search. The second part of the book presents population based methods, such as Estimation Distribution algorithms, Scatter Search, and Genetic Algorithms. The third part covers other advanced techniques, such as Ant Colony Optimization, Co-evolutionary methods, GRASP, and Memetic algorithms. Overall, the book's objective is engineered to provide a broad coverage of the concepts, methods, and tools of this important area of ANNs within the realm of continuous optimization.



Metaheuristics In Machine Learning Theory And Applications


Metaheuristics In Machine Learning Theory And Applications
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Author : Diego Oliva
language : en
Publisher: Springer Nature
Release Date : 2021-07-13

Metaheuristics In Machine Learning Theory And Applications written by Diego Oliva and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-13 with Computers categories.


This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.



Nature Inspired Methods For Metaheuristics Optimization


Nature Inspired Methods For Metaheuristics Optimization
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Author : Fouad Bennis
language : en
Publisher: Springer Nature
Release Date : 2020-01-17

Nature Inspired Methods For Metaheuristics Optimization written by Fouad Bennis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-17 with Business & Economics categories.


This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.



Metaheuristics For Machine Learning


Metaheuristics For Machine Learning
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Author : Mansour Eddaly
language : en
Publisher: Springer Nature
Release Date : 2023-03-13

Metaheuristics For Machine Learning written by Mansour Eddaly and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Computers categories.


Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.



Handbook Of Approximation Algorithms And Metaheuristics


Handbook Of Approximation Algorithms And Metaheuristics
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Author : Teofilo F. Gonzalez
language : en
Publisher: CRC Press
Release Date : 2018-05-15

Handbook Of Approximation Algorithms And Metaheuristics written by Teofilo F. Gonzalez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-15 with Computers categories.


Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.



Metaheuristics


Metaheuristics
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Author : Karl F. Doerner
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-13

Metaheuristics written by Karl F. Doerner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-13 with Mathematics categories.


The aim of Metaheuristics: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field. Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.



Development In Wastewater Treatment Research And Processes


Development In Wastewater Treatment Research And Processes
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Author : Maulin P. Shah
language : en
Publisher: Elsevier
Release Date : 2024-01-20

Development In Wastewater Treatment Research And Processes written by Maulin P. Shah and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-20 with Science categories.


Advanced Oxidation Processes for Tannery Effluent provides a detailed overview of currently applied and tested sewage treatment technologies and he integration of advanced processes to remove trace organic contaminants and micro-organisms. The book discusses the potential of improved biological treatment to produce reusable wastewater, new municipal wastewater disinfection processes and the reduction of bacteria resistant to antibiotics as well as the effects of advanced oxidation processes on microbial and chemical contaminants. Advanced Oxidation Processes for Tannery Effluent features membrane bioreactors, moving bed bioreactors, light and solar technology, ozonation and immobilized heterogeneous photocatalysis, and provides an assessment of the potential of built wetlands integrated with advanced oxidation technologies to ensure wastewater recycling for reuse. The book discusses issues and standards for water reuse, the state of application of membrane bioreactors and the treatment of reverse osmosis concentrate for better water use in wastewater treatment. It presents the latest developments in the field of drinking water reuse and addresses various important issues in this context, such as proper public health protection, reliability and monitoring. - Includes advanced oxidation processes for wastewater treatment - Describes various methodologies to treat tannery effluent - Outlines applications of different types of treatment strategies to cope up with tannery effluent - Applies tertiary advanced oxidation process to remove toxic contaminants from wastewater - Provides biochemical pathways of degraded contaminants through various oxidation processes



Encyclopedia Of Optimization


Encyclopedia Of Optimization
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Author : Christodoulos A. Floudas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-04

Encyclopedia Of Optimization written by Christodoulos A. Floudas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-04 with Mathematics categories.


The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".



Progress In Artificial Intelligence And Pattern Recognition


Progress In Artificial Intelligence And Pattern Recognition
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Author : Yanio Hernández Heredia
language : en
Publisher: Springer Nature
Release Date : 2021-11-03

Progress In Artificial Intelligence And Pattern Recognition written by Yanio Hernández Heredia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-03 with Computers categories.


This book constitutes the refereed proceedings of the 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, held in Havana, Cuba, in October 2021. The 42 full papers presented were carefully reviewed and selected from 73 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis.



Reactive Search And Intelligent Optimization


Reactive Search And Intelligent Optimization
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Author : Roberto Battiti
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-16

Reactive Search And Intelligent Optimization written by Roberto Battiti and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-16 with Business & Economics categories.


Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics. Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities forthe automated tuning of these parameters.