Short description:

Discusses use of applied soft computing techniques in biomedical applications, communication technologies, data analytics and applications, image processing, and natural language processing. Details how soft computing can assist in tackling obstacles associated with signal processing, network optimization, quality of service, and beyond.

Long 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.

Table of Contents:

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