Описание: This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2020, held in Chennai, India, in October 2020. The 12 full papers and 7 short papers presented in this volume were thoroughly reviewed and selected from 40 qualified submissions.
Автор: Bhattacharyya Siddhartha Название: Hybrid Metaheuristics: Research and Applications ISBN: 9813270225 ISBN-13(EAN): 9789813270220 Издательство: World Scientific Publishing Рейтинг: Цена: 17424.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A metaheuristic is a higher-level procedure designed to select a partial search algorithm that may lead to a good solution to an optimization problem, especially with incomplete or imperfect information.
This unique compendium focuses on the insights of hybrid metaheuristics. It illustrates the recent researches on evolving novel hybrid metaheuristic algorithms, and prominently highlights its diverse application areas. As such, the book helps readers to grasp the essentials of hybrid metaheuristics and to address real world problems.
The must-have volume serves as an inspiring read for professionals, researchers, academics and graduate students in the fields of artificial intelligence, robotics and machine learning.
Автор: Kulkarni Anand J., Mezura-Montes Efrйn, Wang Yong Название: Constraint Handling in Metaheuristics and Applications ISBN: 9813367091 ISBN-13(EAN): 9789813367098 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques.
Описание: This book details the designing of hybrid control strategies for practical systems containing time varying uncertainties, disturbances, nonlinearities, unknown parameters, unmodelled dynamics, delays, etc., concurrently. In this book, the advantages of different controllers will be brought together to produce superior control performance for the practical systems. Being aware of the advantages of adaptive controller to tackle unknown constant, time varying uncertainties and time varying disturbances, a variant of adaptive controller, namely L1 adaptive controller, is hybridized with other strategies. In this book, to facilitate optimal parameter setting of the basic L1 adaptive controller, stochastic optimization technique will be hybridized with it. The stability of the optimization technique along with the controller will be guaranteed analytically with the help of spectral radius convergence. The proposed method exhibits satisfactory exploration and exploitation capabilities. Again, this book will throw light on tackling nonlinearities along with uncertainties and disturbances by hybridizing fuzzy logic with L1 adaptive controller. The performances of the designed controllers will be compared with different control methodologies to validate their effectiveness. The overall stability of the nonlinear system with the designed controller will be guaranteed with the help of fuzzy Lyapunov function to retain the zonal behaviour of the system. This fuzzy PDC-L1 adaptive controller is efficient to tackle nonlinearities and at the same time cancels unknown constant, time varying uncertainties and time varying disturbances adequately. This book will also contain four simulation case studies to validate fruitfulness of the designed controllers. To demonstrate the superior control ability of these controllers in tackling practical system, three experimental case studies will also be provided.
Автор: Oliva Diego, Houssein Essam H., Hinojosa Salvador Название: Metaheuristics in Machine Learning: Theory and Applications ISBN: 3030705412 ISBN-13(EAN): 9783030705411 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: 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.
Автор: Jayaraman Valadi; Patrick Siarry Название: Applications of Metaheuristics in Process Engineering ISBN: 3319357042 ISBN-13(EAN): 9783319357041 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatorial optimization and mixed integer optimization.
Описание: This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, held in Trivandrum, India, in December 2019. The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions.
Описание: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems.
Автор: Erik Cuevas; Daniel Zald?var; Marco P?rez-Cisneros Название: Advances in Metaheuristics Algorithms: Methods and Applications ISBN: 3030077365 ISBN-13(EAN): 9783030077365 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Нет в наличии.
Описание:
This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.
Автор: Siddhartha Bhattacharyya Название: Hybrid Metaheuristics for Image Analysis ISBN: 3030084973 ISBN-13(EAN): 9783030084974 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization.The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.
Автор: Christian Blum; G?nther R. Raidl Название: Hybrid Metaheuristics ISBN: 3319308823 ISBN-13(EAN): 9783319308821 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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