Applied Soft Computing Techniques
Theoretical Principles and Practical Applications
1st Edition
Published on 10. July 2025
Book
Hardback
440 pages
978-1-77491-884-5 (ISBN)
Description
Soft computing techniques have the ability to handle complex, uncertain, and imprecise information to create usable solutions to convoluted problems, or those just too time-consuming to solve with current hardware. This new book details the use and applications of soft computing technology in several fields, exploring the use of these techniques in biomedical applications, communication technologies, data analytics and applications, image processing and natural language processing.
The chapters in the section on biomedical applications explore soft computing techniques for cancer data analysis, depression and mental health analysis, heart disease detection, etc. The editors go on to discuss soft computing in communication systems, looking at graphs, design processes, and mapping techniques, as well as the integration of IoT devices, drone technology, etc. The volume also details how soft computing methodologies can assist in tackling the obstacles associated with signal processing, network optimization, quality of service and beyond.
Several chapters discuss the use of soft computing techniques in data compression, handling of large-scaled heterogenous databases, visualization techniques, etc. Applications of soft computing in image processing are also discussed and cover human face recognition, casualty detection, traffic sign recognition, and predicting soil features using satellite imagery. Soft computing techniques in natural language processing consider text-to-speech signal conversion, NLP and speech recognition, speech emotion recognition and more.
This volume will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.
Applied Soft Computing Techniques: Theoretical Principles and Practical Applications will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.
The chapters in the section on biomedical applications explore soft computing techniques for cancer data analysis, depression and mental health analysis, heart disease detection, etc. The editors go on to discuss soft computing in communication systems, looking at graphs, design processes, and mapping techniques, as well as the integration of IoT devices, drone technology, etc. The volume also details how soft computing methodologies can assist in tackling the obstacles associated with signal processing, network optimization, quality of service and beyond.
Several chapters discuss the use of soft computing techniques in data compression, handling of large-scaled heterogenous databases, visualization techniques, etc. Applications of soft computing in image processing are also discussed and cover human face recognition, casualty detection, traffic sign recognition, and predicting soil features using satellite imagery. Soft computing techniques in natural language processing consider text-to-speech signal conversion, NLP and speech recognition, speech emotion recognition and more.
This volume will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.
Applied Soft Computing Techniques: Theoretical Principles and Practical Applications will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.
More details
Language
English
Place of publication
Oakville
Canada
Target group
College/higher education
Professional and scholarly
Academic and Postgraduate
Illustrations
178 s/w Abbildungen, 140 s/w Zeichnungen, 38 s/w Photographien bzw. Rasterbilder, 48 s/w Tabellen
48 Tables, black and white; 140 Line drawings, black and white; 38 Halftones, black and white; 178 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 29 mm
Weight
857 gr
ISBN-13
978-1-77491-884-5 (9781774918845)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Samarjeet Borah | Ratna Raja Kumar Jambi | Sharifah Sakinah Syed Ahmad
Applied Soft Computing Techniques
Theoretical Principles and Practical Applications
E-Book
07/2025
1st Edition
Apple Academic Press Inc.
€225.99
Available for download
Samarjeet Borah | Ratna Raja Kumar Jambi | Sharifah Sakinah Syed Ahmad
Applied Soft Computing Techniques
Theoretical Principles and Practical Applications
E-Book
07/2025
1st Edition
Apple Academic Press Inc.
€225.99
Available for download
Persons
Samarjeet Borah, PhD is Professor and Head in the Department of Computer Applications at SMIT, Sikkim Manipal University, India. He has carried out research projects, published research papers in journals and conferences, and organized workshops and conferences. He is Editor-in-Chief of the book series Research Notes on Computing and Communication Sciences. Dr. Borah has served as a keynote as well as invited speaker at several international conferences. His areas of research are data mining, information security, data science, and machine learning.
Ratna Raja Kumar Jambi, PhD is Principal at the Genba Sopanrao Moze College of Engineering, Balewadi, Pune, India. He has 17 years of teaching and research work. He has patents at both national and international levels and has published papers and book chapters on artificial intelligence and machine learning. He has organized national and international conferences. He received an Innovative Leader Award from the World Education Summit & Awards in 2019 in New Delhi.
Sharifah Sakinah Syed Ahmad, PhD is currently working as Associate Professor in the Department of Intelligent Computing & Analytics (ICA), Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM). Her current research work is on the granular fuzzy rule-based system, evolutionary method, modeling, and data science. Dr. Ahmad has been a member of numerous program committees at national and international conferences in intelligent systems and soft computing, where she is involved in organizing and reviewing activities. She is an editorial board member of the IEEE Transactions on Systems, Man, and Cybernetics: Systems and a member of the Association for Computing Machinery (ACM). She has co-authored numerous journal publications, conference articles, and book chapters. She has also received several grants from various funding agencies, including the Ministry of Education, Malaysia, and the Ministry of Science, Technology, and Innovation, Malaysia. Dr. Ahmad has 15 years of experience in teaching. She was also involved in conducting several workshops related to improving data science and modeling.
Mahendra Prabhakar Deore, PhD is an Assistant Professor of Computer Engineering at MKSSS's Cummins College of Engineering for Women, Pune, India. With over 16 years of dedicated teaching experience at undergraduate level, Dr. Deore has authored and published more than 20 SCI- and SCOPUS-indexed research papers. His primary areas of interest encompass big data, security, computer networks, and machine learning.
Ratna Raja Kumar Jambi, PhD is Principal at the Genba Sopanrao Moze College of Engineering, Balewadi, Pune, India. He has 17 years of teaching and research work. He has patents at both national and international levels and has published papers and book chapters on artificial intelligence and machine learning. He has organized national and international conferences. He received an Innovative Leader Award from the World Education Summit & Awards in 2019 in New Delhi.
Sharifah Sakinah Syed Ahmad, PhD is currently working as Associate Professor in the Department of Intelligent Computing & Analytics (ICA), Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM). Her current research work is on the granular fuzzy rule-based system, evolutionary method, modeling, and data science. Dr. Ahmad has been a member of numerous program committees at national and international conferences in intelligent systems and soft computing, where she is involved in organizing and reviewing activities. She is an editorial board member of the IEEE Transactions on Systems, Man, and Cybernetics: Systems and a member of the Association for Computing Machinery (ACM). She has co-authored numerous journal publications, conference articles, and book chapters. She has also received several grants from various funding agencies, including the Ministry of Education, Malaysia, and the Ministry of Science, Technology, and Innovation, Malaysia. Dr. Ahmad has 15 years of experience in teaching. She was also involved in conducting several workshops related to improving data science and modeling.
Mahendra Prabhakar Deore, PhD is an Assistant Professor of Computer Engineering at MKSSS's Cummins College of Engineering for Women, Pune, India. With over 16 years of dedicated teaching experience at undergraduate level, Dr. Deore has authored and published more than 20 SCI- and SCOPUS-indexed research papers. His primary areas of interest encompass big data, security, computer networks, and machine learning.
Content
Introduction PART I: BIOMEDICAL APPLICATIONS 1. Soft Computing Algorithms and Their Applications in Breast Cancer Data Classification: An Experimental Analysis 2. Real-Time-Based Heart Patient Monitoring System: An Application of Health Care IoT 3. Sentiment and Depression Analysis Using Machine Learning 4. Brain Tumor Detection Using Deep Convolution Neural Networks 5. Smart Healthcare Approach Using Machine Learning for Breast Cancer Diagnosis and Prediction 6. Sedona: A Mental Health Tracker 7. Machine Learning-Based Heart Disease Prediction System 8. Breast Cancer Risk Detection PART II: COMMUNICATION TECHNOLOGIES 9. A Comprehensive Study on Graphs, Design Process, and Mapping Techniques based on Evolutionary Algorithms for Network on Chip Architecture 10. Integrating IoT Devices to Renewable Energy Systems for Increasing Energy Efficiency 11. Architectures of Computer Networks with Standard 12. Drone-Enabled Precision Agriculture: Revolutionizing Crop Management and Yield Optimization PART III: DATA ANALYTICS AND APPLICATIONS 13. Machine Learning-Based Intrusion Detection Techniques: A Concise Study 14. Data Compression for Achieving Cost-Efficient and Secure Data Storage over Public Cloud: A Proposed Model 15. Accessibility of Data Linked to Large Scale Heterogeneous Databases Using Generalized Approach: A Soft Computing-Based Approach 16. Visualization and Comparative Simulation of Pathfinding, Searching, and Sorting Algorithms 17. Educational Website with Search Engine Optimization PART IV: IMAGE PROCESSING 18. A Comparative Analysis on Support Vector Machine, k-Nearest Neighbors, Naive Bayes, and Decision Tree Classifiers Applied for Human Face Recognition 19. Study and Analysis of Computer Vision for Casualty Detection 20. Traffic Sign Recognition Using a Convolutional Neural Network 21. An Optimized Soil Features Prediction Using a Satellite Image Database PART V: NATURAL LANGUAGE PROCESSING 22. A Novel Technique Enabling Text-to-Speech Signal Converting System Using Raspberry Pi 23. Self-Learning Artificial Intelligence Smart Bot with NLP and Speech Recognition 24. Application of Multilayer Perceptron in Speech Emotion Recognition 25. Bangla and Odia Machine Translation Using EM Algorithm: Experimental Evaluation