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E-raamat: Applied Soft Computing: Techniques and Applications [Taylor & Francis e-raamat]

Edited by , Edited by (Sikkim Manipal Inst. of Tech., India)
  • Formaat: 258 pages, 37 Tables, black and white; 6 Line drawings, color; 76 Line drawings, black and white; 5 Halftones, color; 2 Halftones, black and white; 11 Illustrations, color; 78 Illustrations, black and white
  • Ilmumisaeg: 03-Feb-2022
  • Kirjastus: Apple Academic Press Inc.
  • ISBN-13: 9781003186885
  • Taylor & Francis e-raamat
  • Hind: 193,88 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 276,97 €
  • Säästad 30%
  • Formaat: 258 pages, 37 Tables, black and white; 6 Line drawings, color; 76 Line drawings, black and white; 5 Halftones, color; 2 Halftones, black and white; 11 Illustrations, color; 78 Illustrations, black and white
  • Ilmumisaeg: 03-Feb-2022
  • Kirjastus: Apple Academic Press Inc.
  • ISBN-13: 9781003186885
"Applied Soft Computing: Techniques and Applications explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book explores a variety of modern applications in soft computing, including bioinspired computing, reconfigurable computing, fuzzy logic, fusion-based learning, intelligent healthcare systems, bioinformatics, data mining,functional approximation, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing. Soft computing has played a crucial role not only with the theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligent-based applications. Beginning with the basics of soft computing, this book deeply covers applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence. This book is destined for a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications"--

This book explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing.



Applied Soft Computing: Techniques and Applications explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book explores a variety of modern applications in soft computing, including bioinspired computing, reconfigurable computing, fuzzy logic, fusion-based learning, intelligent healthcare systems, bioinformatics, data mining, functional approximation, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, and optimization principles. The book acts as a reference book for AI developers, researchers, and academicians as it addresses the recent technological developments in the field of soft computing.

Soft computing has played a crucial role not only with the theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligent-based applications. Beginning with the basics of soft computing, this book deeply covers applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, meta heuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.

This book is destined for a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

Contributors xv
Abbreviations xix
Preface xxiii
Introduction xxv
1 Swarm Intelligence and Bio-Inspired Computation
1(22)
Rebika Rai
2 User vs. Self-Tuning Optimization: A Case Study on Image Registration
23(18)
Jose Santamaria Lopez
Maria L. Rivero-Cejudo
3 Secure Communication Using a Novel 4-D Double Scroll Chaotic System
41(18)
Pushali Trikha
Lone Seth Jahanzaib
4 Detecting Hate Speech Through Machine Learning
59(10)
F. H. A. Shibly
Uzzal Sharma
H. M. M. Naleer
5 Optimization of Logical Resources in Reconfigurable Computing
69(20)
S. Jamuna
6 A Sophisticated Similarity Measure for Picture Fuzzy Sets and Their Application
89(16)
Palash Dutta
7 Semi-Circular Fuzzy Variable and Its Properties
105(16)
Palash Dutta
8 Virtual Machine Selection Optimization Using Nature-Inspired Algorithms
121(14)
R. B. Madhumala
Harshvardhan Tiwari
9 Extractive Text Summarization Using Convolutional Neural Network
135(18)
Mihir
Chandni Agarwal
Sweta Agarwal
Udit Kr. Chakraborty
10 Theory, Concepts, and Applications of Artificial Neural Network
153(24)
P. Anirudh Hebbar
M. V. Manoj Kumar
Archana Mathur
11 Comparing Word Embeddings on Authorship Identification
177(18)
Tarun Kumar Dugar
S. Gowtham
Udit Kr. Chakraborty
12 Fusion-Based Learning Approach for Predicting Diseases in an Earlier Stage
195(12)
K. Krishna Prasad
P. S. Aithal
A. Jayanthiladevi
Manivel Kandasamy
13 A Fuzzy-Based Framework for an Agriculture Recommender System Using Membership Function
207(18)
R. Narmadha
T. P. Latchoumi
A. Jayanthiladevi
T. L. Yookesh
S. Prince Mary
14 Implying Fuzzy Set for Computing Agricultural Vulnerability
225(12)
A. Jayanthiladevi
L. Devi
R. Kannadasan
Ved P. Mishra
Piyush Mishra
A. Mohamed Uvaze Ahamed
15 Modeling an Intelligent System for Health Care Management
237
A. Jayanthiladevi
P. S. Aithal
K. Krishna Prasad
Manivel Kandasamy
Samarjeet Borah, PhD, is Professor and Head of the Department of Computer Applications, SMIT, Sikkim Manipal University, Sikkim, India. Dr. Borah has carried out various funded projects from AICTE (GoI), DST-CSRI (GoI), etc. He has organized various workshops and conferences at national and international levels. Dr. Borah is involved with various book volumes and journals. He is the editor-in-chief of the book series Research Notes on Computing and Communication Sciences, published by Apple Academic Press. His areas of research are data mining, data science, and machine learning.

Ranjit Panigrahi, PhD, is Assistant Professor in the Department of Computer Applications at Sikkim Manipal University (SMU), Sikkim, India. His research interests are machine learning, pattern recognition, and wireless sensor networks. Dr. Panigrahi is actively involved in various national and international conferences of repute. He serves as a member of technical review committees for various international journals. He received his MTech in Computer Sciences and Engineering from Sikkim Manipal Institute of Technology and his PhD in Computer Applications from Sikkim Manipal University, India.