Nature Inspired Computation In Data Mining And Machine Learning

Nature Inspired Computation In Data Mining And Machine Learning Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Nature Inspired Computation In Data Mining And Machine Learning book. This book definitely worth reading, it is an incredibly well-written.

Nature-Inspired Computation in Data Mining and Machine Learning

Xin-She Yang,Xing-Shi He
Nature Inspired Computation in Data Mining and Machine Learning Book PDF

Author : Xin-She Yang,Xing-Shi He
Publisher : Springer Nature
Page : 273 pages
File Size : 47,7 Mb
Release : 2019-09-03
Category : Technology & Engineering
ISBN : 9783030285531

Get Book

Nature-Inspired Computation in Data Mining and Machine Learning by Xin-She Yang,Xing-Shi He Pdf

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.

Nature Inspired Computing for Data Science

Minakhi Rout,Jitendra Kumar Rout,Himansu Das
Nature Inspired Computing for Data Science Book PDF

Author : Minakhi Rout,Jitendra Kumar Rout,Himansu Das
Publisher : Springer Nature
Page : 303 pages
File Size : 46,9 Mb
Release : 2019-11-26
Category : Computers
ISBN : 9783030338206

Get Book

Nature Inspired Computing for Data Science by Minakhi Rout,Jitendra Kumar Rout,Himansu Das Pdf

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.

Nature-Inspired Computation and Machine Learning

Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro
Nature Inspired Computation and Machine Learning Book PDF

Author : Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro
Publisher : Springer
Page : 522 pages
File Size : 52,5 Mb
Release : 2014-11-05
Category : Computers
ISBN : 9783319136509

Get Book

Nature-Inspired Computation and Machine Learning by Alexander Gelbukh,Félix Castro Espinoza,Sofía N. Galicia-Haro Pdf

The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.

Nature-Inspired Algorithms and Applications

S. Balamurugan,Anupriya Jain,Sachin Sharma,Dinesh Goyal,Sonia Duggal,Seema Sharma
Nature Inspired Algorithms and Applications Book PDF

Author : S. Balamurugan,Anupriya Jain,Sachin Sharma,Dinesh Goyal,Sonia Duggal,Seema Sharma
Publisher : John Wiley & Sons
Page : 388 pages
File Size : 44,8 Mb
Release : 2021-12-14
Category : Computers
ISBN : 9781119681748

Get Book

Nature-Inspired Algorithms and Applications by S. Balamurugan,Anupriya Jain,Sachin Sharma,Dinesh Goyal,Sonia Duggal,Seema Sharma Pdf

NATURE-INSPIRED ALGORITHMS AND APPLICATIONS The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide. Among the subjects of the 12 chapters are: A novel method based on TRIZ to map real-world problems to nature problems Applications of cuckoo search algorithm for optimization problems Performance analysis of nature-inspired algorithms in breast cancer diagnosis Nature-inspired computation in data mining Hybrid bat-genetic algorithm–based novel optimal wavelet filter for compression of image data Efficiency of finding best solutions through ant colony optimization techniques Applications of hybridized algorithms and novel algorithms in the field of machine learning. Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.

Nature-Inspired Computation in Engineering

Xin-She Yang
Nature Inspired Computation in Engineering Book PDF

Author : Xin-She Yang
Publisher : Springer
Page : 276 pages
File Size : 51,9 Mb
Release : 2016-03-19
Category : Technology & Engineering
ISBN : 9783319302355

Get Book

Nature-Inspired Computation in Engineering by Xin-She Yang Pdf

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms, discrete firefly algorithm, discrete cuckoo search, plant propagation algorithm, parameter-free bat algorithm, gravitational search, biogeography-based algorithm, differential evolution, particle swarm optimization and others. Applications include vehicle routing, swarming robots, discrete and combinatorial optimization, clustering of wireless sensor networks, cell formation, economic load dispatch, metamodeling, surrogated-assisted cooperative co-evolution, data fitting and reverse engineering as well as other case studies in engineering. This book will be an ideal reference for researchers, lecturers, graduates and engineers who are interested in nature-inspired computation, artificial intelligence and computational intelligence. It can also serve as a reference for relevant courses in computer science, artificial intelligence and machine learning, natural computation, engineering optimization and data mining.

Nature-Inspired Algorithms for Big Data Frameworks

Banati, Hema,Mehta, Shikha,Kaur, Parmeet
Nature Inspired Algorithms for Big Data Frameworks Book PDF

Author : Banati, Hema,Mehta, Shikha,Kaur, Parmeet
Publisher : IGI Global
Page : 412 pages
File Size : 46,6 Mb
Release : 2018-09-28
Category : Computers
ISBN : 9781522558538

Get Book

Nature-Inspired Algorithms for Big Data Frameworks by Banati, Hema,Mehta, Shikha,Kaur, Parmeet Pdf

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.

Nature-Inspired Computation and Swarm Intelligence

Xin-She Yang
Nature Inspired Computation and Swarm Intelligence Book PDF

Author : Xin-She Yang
Publisher : Academic Press
Page : 442 pages
File Size : 54,8 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9780128197141

Get Book

Nature-Inspired Computation and Swarm Intelligence by Xin-She Yang Pdf

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

Foundations of Computational Intelligence

Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho
Foundations of Computational Intelligence Book PDF

Author : Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho
Publisher : Springer
Page : 396 pages
File Size : 50,7 Mb
Release : 2009-04-30
Category : Technology & Engineering
ISBN : 9783642010880

Get Book

Foundations of Computational Intelligence by Ajith Abraham,Aboul-Ella Hassanien,André Ponce de Leon F. de Carvalho Pdf

Foundations of Computational Intelligence Volume 4: Bio-Inspired Data Mining Theoretical Foundations and Applications Recent advances in the computing and electronics technology, particularly in sensor devices, databases and distributed systems, are leading to an exponential growth in the amount of data stored in databases. It has been estimated that this amount doubles every 20 years. For some applications, this increase is even steeper. Databases storing DNA sequence, for example, are doubling their size every 10 months. This growth is occurring in several applications areas besides bioinformatics, like financial transactions, government data, environmental mo- toring, satellite and medical images, security data and web. As large organizations recognize the high value of data stored in their databases and the importance of their data collection to support decision-making, there is a clear demand for - phisticated Data Mining tools. Data mining tools play a key role in the extraction of useful knowledge from databases. They can be used either to confirm a parti- lar hypothesis or to automatically find patterns. In the second case, which is - lated to this book, the goal may be either to describe the main patterns present in dataset, what is known as descriptive Data Mining or to find patterns able to p- dict behaviour of specific attributes or features, known as predictive Data Mining. While the first goal is associated with tasks like clustering, summarization and association, the second is found in classification and regression problems.

Introduction to Algorithms for Data Mining and Machine Learning

Xin-She Yang
Introduction to Algorithms for Data Mining and Machine Learning Book PDF

Author : Xin-She Yang
Publisher : Academic Press
Page : 188 pages
File Size : 51,7 Mb
Release : 2019-07-15
Category : Mathematics
ISBN : 9780128172162

Get Book

Introduction to Algorithms for Data Mining and Machine Learning by Xin-She Yang Pdf

Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages

Nature-Inspired Computation

Mario D'Acunto
Nature Inspired Computation Book PDF

Author : Mario D'Acunto
Publisher : Unknown
Page : 194 pages
File Size : 50,5 Mb
Release : 2015
Category : Biocomplexity
ISBN : 1634824768

Get Book

Nature-Inspired Computation by Mario D'Acunto Pdf

Nature inspired computation is an old idea, first proposed in the early fifties by Alan Turing, one of the founders of computer science. Turing suggested computational models of pattern formation in living systems based on systems of coupled reaction-diffusion equations giving rise to spatial patterns due to self-organization of substances in chemical concentrations. Since the pioneering work by Turing, many optimization algorithms stimulated by real-world features have gained great popularity and impact, thanks to their efficiency in solving nonlinear design problems. Nature-inspired computation has permeated into almost all areas of sciences, engineering and industries, from data mining to optimization, from computational intelligence to signal processing, from image analysis and vision systems to industrial applications. The book provides an introductory tour of the most popular nature inspired computational strategies. The book is subdivided in two parts, briefly describing the inspiration and motivation of natural processes and phenomena, main players, design principles, the scope of each branch, current trends and open problems. In the first section, attention is focused on Artificial and Spiking Neural Networks (Chapter 2), Evolutionary and Genetic Algorithms (Chapter 3), and Swarm Intelligence algorithms (Chapter 4). In the second section, we present the emergent knowledge and technologies in Multiscale Nature processes (Chapter 5), Quantum Computing and Quantum Cryptography (Chapter 6), Encryption and Secure Communication system (Chapter 7), Image processing and Vision systems (Chapter 8), and finally on Nanophotonics Information (Chapter 9).

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

Simon James Fong,Richard C. Millham
Bio inspired Algorithms for Data Streaming and Visualization Big Data Management and Fog Computing Book PDF

Author : Simon James Fong,Richard C. Millham
Publisher : Springer Nature
Page : 228 pages
File Size : 49,9 Mb
Release : 2020-08-25
Category : Technology & Engineering
ISBN : 9789811566950

Get Book

Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing by Simon James Fong,Richard C. Millham Pdf

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.

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Management Association, Information Resources
Nature Inspired Computing Concepts Methodologies Tools and Applications Book PDF

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1780 pages
File Size : 45,6 Mb
Release : 2016-07-26
Category : Computers
ISBN : 9781522507895

Get Book

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf

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.

Transactions on Computational Science XXI

Marina L. Gavrilova,C.J. Kenneth Tan,Ajith Abraham
Transactions on Computational Science XXI Book PDF

Author : Marina L. Gavrilova,C.J. Kenneth Tan,Ajith Abraham
Publisher : Springer
Page : 367 pages
File Size : 49,6 Mb
Release : 2013-11-25
Category : Computers
ISBN : 9783642453182

Get Book

Transactions on Computational Science XXI by Marina L. Gavrilova,C.J. Kenneth Tan,Ajith Abraham Pdf

This, the 21st issue of the Transactions on Computational Science journal, edited by Ajith Abraham, is devoted to the topic of nature-inspired computing and applications. The 15 full papers included in the volume focus on the topics of neurocomputing, evolutionary algorithms, swarm intelligence, artificial immune systems, membrane computing, computing with words, artificial life and hybrid approaches.

Nature-Inspired Computation and Swarm Intelligence

Xin-She Yang
Nature Inspired Computation and Swarm Intelligence Book PDF

Author : Xin-She Yang
Publisher : Academic Press
Page : 444 pages
File Size : 44,7 Mb
Release : 2020-04-09
Category : Computers
ISBN : 9780128226094

Get Book

Nature-Inspired Computation and Swarm Intelligence by Xin-She Yang Pdf

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

Nature-Inspired Optimization Algorithms

Xin-She Yang
Nature Inspired Optimization Algorithms Book PDF

Author : Xin-She Yang
Publisher : Academic Press
Page : 312 pages
File Size : 49,6 Mb
Release : 2020-09-09
Category : Science
ISBN : 9780128219898

Get Book

Nature-Inspired Optimization Algorithms by Xin-She Yang Pdf

Nature-Inspired Optimization Algorithms, Second Edition provides an 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 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, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding and practical implementation hints Presents a step-by-step introduction to each algorithm Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications