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.
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.
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 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: 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: 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 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.
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.
Discover a thorough exploration of how to use computational, algorithmic, statistical, and informatics methods to analyze digital data
Informatics and Machine Learning: From Martingales to Metaheuristics delivers an interdisciplinary presentation on how analyze any data captured in digital form. The book describes how readers can conduct analyses of text, general sequential data, experimental observations over time, stock market and econometric histories, or symbolic data, like genomes. It contains large amounts of sample code to demonstrate the concepts contained within and assist with various levels of project work.
The book offers a complete presentation of the mathematical underpinnings of a wide variety of forms of data analysis and provides extensive examples of programming implementations. It is based on two decades worth of the distinguished author's teaching and industry experience.
A thorough introduction to probabilistic reasoning and bioinformatics, including Python shell scripting to obtain data counts, frequencies, probabilities, and anomalous statistics, or use with Bayes' rule
An exploration of information entropy and statistical measures, including Shannon entropy, relative entropy, maximum entropy (maxent), and mutual information
A practical discussion of ad hoc, ab initio, and bootstrap signal acquisition methods, with examples from genome analytics and signal analytics
Perfect for undergraduate and graduate students in machine learning and data analytics programs, Informatics and Machine Learning: From Martingales to Metaheuristics will also earn a place in the libraries of mathematicians, engineers, computer scientists, and life scientists with an interest in those subjects.
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: Joining in the centenary celebration of the life and work of Alan Turing, this book reviews the latest developments in artificial intelligence, evolutionary computation and metaheuristics, all of which can be traced back to Turing`s pioneer work.
Описание: This book explores hot topics in the design, administration and management of dynamic grid environments. The emphasis is on preferences and autonomous decisions of system users, secure access to processed data and services and the use of green technologies.
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