Machine Learning and Metaheuristics: Methods and Analysis, Dulhare
Автор: Taymaz Akan, Ahmed M. Anter, A. ?ima Etaner-Uyar, Название: Engineering Applications of Modern Metaheuristics ISBN: 3031168313 ISBN-13(EAN): 9783031168314 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities.
Автор: Eddaly Название: Metaheuristics for Machine Learning ISBN: 9811938873 ISBN-13(EAN): 9789811938870 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Bhattacharyya Название: Hybrid Metaheuristics for Image Analysis ISBN: 331977624X ISBN-13(EAN): 9783319776248 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Current and Future Trends in Segmenting Satellite Images Using Hybrid and Dynamic Genetic Algorithms.- A Hybrid Metaheuristic Algorithm Based on Quantum Genetic Computing for Image Segmentation.- Genetic Algorithm Implementation to Optimize the Hybridization of Feature Extraction and Metaheuristic Classifiers.- Optimization of a HMM-Based Hand Gesture Recognition System Using a Hybrid Cuckoo Search Algorithm.- Satellite Image Contrast Enhancement Using Fuzzy Termite Colony Optimization.- Image Segmentation Using Metaheuristic-Based DeformableModels.- Hybridization of the Univariate Marginal Distribution Algorithm with Simulated Annealing for Parametric Parabola Detection.- Image Thresholding Based on Fuzzy Particle Swarm Optimization.- Hybrid Metaheuristics Applied to Image Reconstruction for an Electrical Impedance Tomography Prototype.
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: Abdel-Basset,Mohamed Название: Metaheuristics Algorithms For Medical Applications ISBN: 044313314X ISBN-13(EAN): 9780443133145 Издательство: Elsevier Science Рейтинг: Цена: 23244.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on civil and structural engineering and construction management applications. The contributions constitute modified, extended and improved versions of research presented at the minisymposium organized by the editors at the ECCOMAS conference on this topic in Barcelona 2014.
Автор: Yossi Borenstein; Alberto Moraglio Название: Theory and Principled Methods for the Design of Metaheuristics ISBN: 3662519550 ISBN-13(EAN): 9783662519554 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes methods for incorporating problem knowledge in evolutionary algorithms and other metaheuristics, and shows how statistical methods can use experimental data to enhance the performance of existing metaheuristics in a systematic way.
Описание: This book focuses on civil and structural engineering and construction management applications. The contributions constitute modified, extended and improved versions of research presented at the minisymposium organized by the editors at the ECCOMAS conference on this topic in Barcelona 2014.
Автор: Johann Dr?o; A. Chatterjee; Alain P?trowski; Patri Название: Metaheuristics for Hard Optimization ISBN: 364206194X ISBN-13(EAN): 9783642061943 Издательство: Springer Рейтинг: Цена: 13969.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains case studies from engineering and operations researchIncludes commented literature for each chapter
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: Fouad Bennis; Rajib Kumar Bhattacharjya Название: Nature-Inspired Methods for Metaheuristics Optimization ISBN: 3030264572 ISBN-13(EAN): 9783030264574 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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.
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