Overview
- Presents improved fuzzy sets and intelligent and optimization algorithms
- Bridges between data science, machine learning and soft computing methods
- Covers applications of metaheuristics in medical imaging and dynamical system control
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 413)
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Table of contents (9 chapters)
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Front Matter
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Fuzzy Logic Implication and Usage in Text Classification and Medical Data Analytics
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Front Matter
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Fuzzy Driven Optimization Methods and Control Systems
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Front Matter
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Keywords
- Social Spider Optimization
- Fuzzy Logic in Computational Biology
- Gravitational Search Algorithm
- Medical Image Classification
- Fuzzy Wavelet Neural Network
- Generative Adversarial Networks
- Hybrid Optimization Algorithms
- Data Classification with Deep Learning
- Data-driven Fuzzy Control
- Fuzzy Rough Set Nearest Neighbour
About this book
This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control.
The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design ofhybrid algorithms for applications in data analytics, classification model, and engineering control.
Editors and Affiliations
Bibliographic Information
Book Title: Soft Computing for Data Analytics, Classification Model, and Control
Editors: Deepak Gupta, Aditya Khamparia, Ashish Khanna, Oscar Castillo
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-030-92026-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-92025-8Published: 31 January 2022
Softcover ISBN: 978-3-030-92028-9Published: 01 February 2023
eBook ISBN: 978-3-030-92026-5Published: 30 January 2022
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: VIII, 165
Number of Illustrations: 22 b/w illustrations, 61 illustrations in colour
Topics: Computational Intelligence, Data Structures and Information Theory, Artificial Intelligence, Bioinformatics, Control and Systems Theory