How to Design Optimization Algorithms by Applying Natural Behavioral Patterns PDF Download
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Author: Rohollah Omidvar
Publisher: Bentham Science Publishers
ISBN: 9811459576
Category : Computers
Languages : en
Pages : 209
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Book Description
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference to students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena.
Author: Rohollah Omidvar
Publisher: Bentham Science Publishers
ISBN: 9811459576
Category : Computers
Languages : en
Pages : 209
Get Book Here
Book Description
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns is a guide book that introduces readers to optimization algorithms based on natural language processing. Readers will learn about the basic concept of optimization, optimization algorithm fundamentals and the methods employed to formulate natural ideas and behaviors into algorithms. Readers will learn how to create their own algorithm from the information provided in the text. The book is a simple reference to students and programming enthusiasts who are interested in learning about optimization and the process of designing algorithms designed to mimic natural phenomena.
Author: Dipti Singh
Publisher: Springer Nature
ISBN: 3031179293
Category : Technology & Engineering
Languages : en
Pages : 211
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Book Description
This book gives a detailed information of various real-life applications from various fields using nature inspired optimization techniques. These techniques are proven to be efficient and robust in many difficult problems in literature. The authors provide detailed information about real-life problems and how various nature inspired optimizations are applied to solve these problems. The authors discuss techniques such as Biogeography Based Optimization, Glow Swarm Optimization, Elephant herd Optimization Algorithm, Cuckoo Search Algorithm, Ant Colony Optimization, and Grey Wolf Optimization etc. These algorithms are applied to a wide range of problems from the field of engineering, finance, medicinal etc. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in nature inspired optimization, inspiring women and men, girls and boys to enter and apply themselves to the field.
Author: Xin-She Yang
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 276
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Book Description
Author: Xin-She Yang
Publisher: Springer
ISBN: 3319676695
Category : Technology & Engineering
Languages : en
Pages : 332
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Book Description
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
Author: Anthony Brabazon
Publisher: Springer
ISBN: 9783030096403
Category :
Languages : en
Pages : 498
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Book Description
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.
Author: Omid Bozorg-Haddad
Publisher: Springer
ISBN: 9811052212
Category : Technology & Engineering
Languages : en
Pages : 166
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Book Description
This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.
Author: Shi Cheng
Publisher: Springer
ISBN: 3030150704
Category : Technology & Engineering
Languages : en
Pages : 299
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Book Description
Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence. This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.
Author: Fevrier Valdez
Publisher: Springer Nature
ISBN: 3031473698
Category : Technology & Engineering
Languages : en
Pages : 84
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Book Description
This book provides two new optimization algorithms to address real optimization problems. Optimization is a fundamental concept in engineering and science, and its applications are needed in many fields. From designing products and systems to developing algorithms and models, optimization plays a critical role in achieving efficient and effective solutions to complex problems. Optimization algorithms inspired by nature have proven effective in solving a wide range of problems, including those in engineering, finance, and machine learning. These algorithms are often used when traditional optimization techniques are impractical due to the size or complexity of the problem. In this book, we are presenting two new optimization algorithms inspired by plant roots and the Mycorrhiza Network. The first algorithm is called the Continuous Mycorrhiza Optimization Algorithm (CMOA), which was proposed based on the model of the Continuous Lotka-Volterra System Equations. The second algorithm is called the Discrete Mycorrhiza Optimization Algorithm (DMOA), which design based on the model of Discrete Lotka-Volterra System Equations. By mastering the proposed algorithms, the readers able to develop innovative solutions that improve efficiency, reduce costs, and improve performance in the corresponding field of work.
Author: Serdar Carbas
Publisher: Springer Nature
ISBN: 9813367733
Category : Technology & Engineering
Languages : en
Pages : 420
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Book Description
This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.
Author: Bhabesh Deka
Publisher: Springer Nature
ISBN: 3030348695
Category : Computers
Languages : en
Pages : 678
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Book Description
The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.
