Applied Soft Computing

Techniques and Applications
Taylor & Francis Ltd (Verlag)
  • 1. Auflage
  • |
  • erscheint ca. am 3. Februar 2022
  • |
  • 258 Seiten
E-Book | PDF ohne DRM | Systemvoraussetzungen
978-1-000-40663-4 (ISBN)
This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.

Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern 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, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.

This book will be helpful to 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.
1. Auflage
  • Englisch
  • London
  • |
  • Großbritannien
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6 Line drawings, color; 76 Line drawings, black and white; 5 Halftones, color; 2 Halftones, black and white; 37 Tables, black and white; 11 Illustrations, color; 78 Illustrations, black and white
978-1-000-40663-4 (9781000406634)

weitere Ausgaben werden ermittelt
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.
1. Swarm Intelligence and Bio-Inspired Computation
Rebika Rai
2. User vs. Self-Tuning Optimization: A Case Study on Image Registration
Jose Santamaria Lopez and Maria L. Rivero-Cejudo
3. Secure Communication Using a Novel 4-D Double Scroll Chaotic System
Pushali Trikha and Lone Seth Jahanzaib
4. Detecting Hate Speech Through Machine Learning
F. H. A. Shibly, Uzzal Sharma, and H. M. M. Naleer
5. Optimization of Logical Resources in Reconfigurable Computing
S. Jamuna
6. A Sophisticated Similarity Measure for Picture Fuzzy Sets and Their Application
Palash Dutta
7. Semi-Circular Fuzzy Variable and Its Properties
Palash Dutta
8. Virtual Machine Selection Optimization Using Nature-Inspired Algorithms
R. B. Madhumala and Harshvardhan Tiwari
9. Extractive Text Summarization Using Convolutional Neural Network
Mihir, Chandni Agarwal, Sweta Agarwal, and Udit Kr. Chakraborty
10. Theory, Concepts, and Applications of Artificial Neural Networks
P. Anirudh Hebbar, M. V. Manoj Kumar, and Archana Mathur
11. Comparing Word Embeddings on Authorship Identification
Tarun Kumar Dugar, S. Gowtham, and Udit Kr. Chakraborty
12. Fusion-Based Learning Approach for Predicting Diseases in an Earlier Stage
K. Krishna Prasad, P. S. Aithal, A. Jayanthiladevi, and Manivel Kandasamy
13. A Fuzzy-Based Framework for an Agriculture Recommender System Using Membership Function
R. Narmadha, T. P. Latchoumi, A. Jayanthiladevi, T. L. Yookesh, and S. Prince Mary
14. Implying Fuzzy Set for Computing Agricultural Vulnerability
A. Jayanthiladevi, L. Devi, R. Kannadasan, Ved P. Mishra, Piyush Mishra, and A. Mohamed Uvaze Ahamed
15. Modeling an Intelligent System for Health Care Management
A. Jayanthiladevi, P. S. Aithal, K. Krishna Prasad, and Manivel Kandasamy

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