Hybrid Metaheuristics Research And Applications
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Hybrid Metaheuristics: Research And Applications
Author: Siddhartha Bhattacharyya
language: en
Publisher: World Scientific
Release Date: 2018-09-28
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.Related Link(s)
Hybrid Quantum Metaheuristics
Author: Siddhartha Bhattacharyya
language: en
Publisher: CRC Press
Release Date: 2022-05-07
The reference text introduces the principles of quantum mechanics to evolve hybrid metaheuristics-based optimization techniques useful for real world engineering and scientific problems. The text covers advances and trends in methodological approaches, theoretical studies, mathematical and applied techniques related to hybrid quantum metaheuristics and their applications to engineering problems. The book will be accompanied by additional resources including video demonstration for each chapter. It will be a useful text for graduate students and professional in the field of electrical engineering, electronics and communications engineering, and computer science engineering, this text: Discusses quantum mechanical principles in detail. Emphasizes the recent and upcoming hybrid quantum metaheuristics in a comprehensive manner. Provides comparative statistical test analysis with conventional hybrid metaheuristics. Highlights real-life case studies, applications, and video demonstrations.
Applications of Hybrid Metaheuristic Algorithms for Image Processing
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.