Bio-Inspired Computational Algorithms and Their Applications
Bio-Inspired Computational Algorithms and Their Applications

Author: Shangce Gao

Publisher: BoD – Books on Demand

Published: 2012-03-07

Total Pages: 436

ISBN-13: 9535102141

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Bio-inspired computational algorithms are always hot research topics in artificial intelligence communities. Biology is a bewildering source of inspiration for the design of intelligent artifacts that are capable of efficient and autonomous operation in unknown and changing environments. It is difficult to resist the fascination of creating artifacts that display elements of lifelike intelligence, thus needing techniques for control, optimization, prediction, security, design, and so on. Bio-Inspired Computational Algorithms and Their Applications is a compendium that addresses this need. It integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems. The works presented in this book give insights into the creation of innovative improvements over algorithm performance, potential applications on various practical tasks, and combination of different techniques. The book provides a reference to researchers, practitioners, and students in both artificial intelligence and engineering communities, forming a foundation for the development of the field.

Swarm Intelligence and Bio-Inspired Computation
Swarm Intelligence and Bio-Inspired Computation

Author: Xin-She Yang

Publisher: Newnes

Published: 2013-05-16

Total Pages: 445

ISBN-13: 0124051774

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Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. - Focuses on the introduction and analysis of key algorithms - Includes case studies for real-world applications - Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Handbook of Bioinspired Algorithms and Applications
Handbook of Bioinspired Algorithms and Applications

Author: Stephan Olariu

Publisher: CRC Press

Published: 2005-09-29

Total Pages: 684

ISBN-13: 1420035061

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The mystique of biologically inspired (or bioinspired) paradigms is their ability to describe and solve complex relationships from intrinsically very simple initial conditions and with little or no knowledge of the search space. Edited by two prominent, well-respected researchers, the Handbook of Bioinspired Algorithms and Applications reveals the

Bio-inspired Algorithms for Engineering
Bio-inspired Algorithms for Engineering

Author: Nancy Arana-Daniel

Publisher: Butterworth-Heinemann

Published: 2018-02-03

Total Pages: 154

ISBN-13: 0128137894

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Bio-inspired Algorithms for Engineering builds a bridge between the proposed bio-inspired algorithms developed in the past few decades and their applications in real-life problems, not only in an academic context, but also in the real world. The book proposes novel algorithms to solve real-life, complex problems, combining well-known bio-inspired algorithms with new concepts, including both rigorous analyses and unique applications. It covers both theoretical and practical methodologies, allowing readers to learn more about the implementation of bio-inspired algorithms. This book is a useful resource for both academic and industrial engineers working on artificial intelligence, robotics, machine learning, vision, classification, pattern recognition, identification and control. - Presents real-time implementation and simulation results for all the proposed schemes - Offers a comparative analysis and rigorous analysis of the convergence of proposed algorithms - Provides a guide for implementing each application at the end of each chapter - Includes illustrations, tables and figures that facilitate the reader's comprehension of the proposed schemes and applications

Bio-Inspired Computation in Telecommunications
Bio-Inspired Computation in Telecommunications

Author: Xin-She Yang

Publisher: Morgan Kaufmann

Published: 2015-02-11

Total Pages: 349

ISBN-13: 0128017430

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Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.

Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing
Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing

Author: Simon James Fong

Publisher: Springer Nature

Published: 2020-08-25

Total Pages: 228

ISBN-13: 981156695X

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This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.

Bio-Inspired Computation and Applications in Image Processing
Bio-Inspired Computation and Applications in Image Processing

Author: Xin-She Yang

Publisher: Academic Press

Published: 2016-08-09

Total Pages: 376

ISBN-13: 012804537X

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Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field. In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue. - Reviews the latest developments in bio-inspired computation in image processing - Focuses on the introduction and analysis of the key bio-inspired methods and techniques - Combines theory with real-world applications in image processing - Helps solve complex problems in image and signal processing - Contains a diverse range of self-contained case studies in real-world applications

Nature-Inspired Computation and Swarm Intelligence
Nature-Inspired Computation and Swarm Intelligence

Author: Xin-She Yang

Publisher: Academic Press

Published: 2020-04-10

Total Pages: 442

ISBN-13: 0128197145

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Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.

Bio-Inspired Computing for Information Retrieval Applications
Bio-Inspired Computing for Information Retrieval Applications

Author: Acharjya, D.P.

Publisher: IGI Global

Published: 2017-02-14

Total Pages: 411

ISBN-13: 1522523766

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The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary studies on data processing, swarm-based clustering, and evolutionary computation, this publication is an ideal reference source for researchers, academics, professionals, students, and practitioners.

Nature-Inspired Computing and Optimization
Nature-Inspired Computing and Optimization

Author: Srikanta Patnaik

Publisher: Springer

Published: 2017-03-07

Total Pages: 506

ISBN-13: 3319509209

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The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.