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Nature Inspired Computing For Data Science
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Book Synopsis Nature Inspired Computing for Data Science by : Minakhi Rout
Download or read book Nature Inspired Computing for Data Science written by Minakhi Rout and published by Springer Nature. This book was released on 2019-11-26 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
Book Synopsis Nature-Inspired Computation and Swarm Intelligence by : Xin-She Yang
Download or read book Nature-Inspired Computation and Swarm Intelligence written by Xin-She Yang and published by Academic Press. This book was released on 2020-04-24 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others
Book Synopsis Nature-Inspired Computation in Data Mining and Machine Learning by : Xin-She Yang
Download or read book Nature-Inspired Computation in Data Mining and Machine Learning written by Xin-She Yang and published by Springer Nature. This book was released on 2019-09-03 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
Book Synopsis Nature-Inspired Computing and Optimization by : Srikanta Patnaik
Download or read book Nature-Inspired Computing and Optimization written by Srikanta Patnaik and published by Springer. This book was released on 2017-03-07 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nature-Inspired Computing for Smart Application Design by : Santosh Kumar Das
Download or read book Nature-Inspired Computing for Smart Application Design written by Santosh Kumar Das and published by Springer Nature. This book was released on 2021-03-17 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses primarily on the nature-inspired approach for designing smart applications. It includes several implementation paradigms such as design and path planning of wireless network, security mechanism and implementation for dynamic as well as static nodes, learning method of cloud computing, data exploration and management, data analysis and optimization, decision taking in conflicting environment, etc. The book fundamentally highlights the recent research advancements in the field of engineering and science.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1522507892 Total Pages :1780 pages Book Rating :4.5/5 (225 download)
Book Synopsis Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-07-26 with total page 1780 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.
Book Synopsis Nature-Inspired Algorithms for Big Data Frameworks by : Banati, Hema
Download or read book Nature-Inspired Algorithms for Big Data Frameworks written by Banati, Hema and published by IGI Global. This book was released on 2018-09-28 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.
Book Synopsis Biologically-Inspired Computing for the Arts: Scientific Data through Graphics by : Ursyn, Anna
Download or read book Biologically-Inspired Computing for the Arts: Scientific Data through Graphics written by Ursyn, Anna and published by IGI Global. This book was released on 2012-04-30 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book comprises a collection of authors' individual approaches to the relationship between nature, science, and art created with the use of computers, discussing issues related to the use of visual language in communication about biologically-inspired scientific data, visual literacy in science, and application of practitioner's approach"--Provided by publisher.
Book Synopsis Nature-Inspired Optimization Algorithms by : Aditya Khamparia
Download or read book Nature-Inspired Optimization Algorithms written by Aditya Khamparia and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-02-08 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations
Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang
Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm
Book Synopsis Applications of Nature-Inspired Computing in Renewable Energy Systems by : Mellal, Mohamed Arezki
Download or read book Applications of Nature-Inspired Computing in Renewable Energy Systems written by Mellal, Mohamed Arezki and published by IGI Global. This book was released on 2021-12-17 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems. Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students.
Book Synopsis Nature-Inspired Computing Paradigms in Systems by : Mohamed Arezki Mellal
Download or read book Nature-Inspired Computing Paradigms in Systems written by Mohamed Arezki Mellal and published by Academic Press. This book was released on 2021-06-18 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) covers several areas that include bioinspired techniques and optimization approaches for system dependability. The book addresses the issue of integration and interaction of the bioinspired techniques in system dependability computing so that intelligent decisions, design, and architectures can be supported. It brings together these emerging areas under the umbrella of bio- and nature-inspired computational intelligence. The primary audience of this book includes experts and developers who want to deepen their understanding of bioinspired computing in basic theory, algorithms, and applications. The book is also intended to be used as a textbook for masters and doctoral students who want to enhance their knowledge and understanding of the role of bioinspired techniques in system dependability. Provides the latest review Covers various nature-inspired techniques applied to RAMS+C and PHM problems Includes techniques applied to new applications
Book Synopsis Handbook of Nature-Inspired and Innovative Computing by : Albert Y. Zomaya
Download or read book Handbook of Nature-Inspired and Innovative Computing written by Albert Y. Zomaya and published by Springer Science & Business Media. This book was released on 2006-01-10 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena. Neural networks, evolution-based models, quantum computing, and DNA-based computing and simulations are all a necessary part of modern computing analysis and systems development. Vast literature exists on these new paradigms and their implications for a wide array of applications. This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.
Book Synopsis Handbook of Research on Soft Computing and Nature-Inspired Algorithms by : Shandilya, Shishir K.
Download or read book Handbook of Research on Soft Computing and Nature-Inspired Algorithms written by Shandilya, Shishir K. and published by IGI Global. This book was released on 2017-03-10 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.
Book Synopsis Nature-Inspired Computation and Swarm Intelligence by : Xin-She Yang
Download or read book Nature-Inspired Computation and Swarm Intelligence written by Xin-She Yang and published by Academic Press. This book was released on 2020-04-09 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others
Book Synopsis Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms by : Dash, Sujata
Download or read book Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms written by Dash, Sujata and published by IGI Global. This book was released on 2017-08-10 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
Book Synopsis Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing by : Simon James Fong
Download or read book Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing written by Simon James Fong and published by Springer Nature. This book was released on 2020-08-25 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
