Автор: Cuevas Erik, Galvez Jorge, Avalos Omar Название: Recent Metaheuristics Algorithms for Parameter Identification ISBN: 3030289168 ISBN-13(EAN): 9783030289164 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems.
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.
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 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: Erik Cuevas; Emilio Barocio Espejo; Arturo Conde E Название: Metaheuristics Algorithms in Power Systems ISBN: 3030115925 ISBN-13(EAN): 9783030115920 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.
Описание: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems.
Автор: Toshihide Ibaraki; Koji Nonobe; Mutsunori Yagiura Название: Metaheuristics: ISBN: 1441937900 ISBN-13(EAN): 9781441937902 Издательство: Springer Рейтинг: Цена: 18904.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field.
Автор: Fouad Bennis; Rajib Kumar Bhattacharjya Название: Nature-Inspired Methods for Metaheuristics Optimization ISBN: 3030264572 ISBN-13(EAN): 9783030264574 Издательство: Springer Рейтинг: Цена: 15855.00 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.
Автор: Kulkarni Anand J., Singh Pramod Kumar, Satapathy Suresh Chandra Название: Socio-Cultural Inspired Metaheuristics ISBN: 9811365717 ISBN-13(EAN): 9789811365713 Издательство: Springer Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions.
Описание: This volume presents meta-heuristics approaches for Grid scheduling problems. It brings new ideas, analysis, implementations and evaluation of meta-heuristic techniques for Grid scheduling, which make this volume novel in several aspects.
Автор: Meera Ramadas; Ajith Abraham Название: Metaheuristics for Data Clustering and Image Segmentation ISBN: 3030040968 ISBN-13(EAN): 9783030040963 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
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