Machine Learning and Metaheuristics: Methods and Analysis

✍ Scribed by Uma N. Dulhare; Essam Halim Houssein

• Publisher: Springer Nature Singapore
• Year: 2023
• Tongue: English
• Leaves: 520
• Category: Library

✦ Synopsis

This book takes a balanced approach between theoretical understanding and real-time applications. All the topics included real-world problems which show how to explore, build, evaluate, and optimize machine learning models fusion with metaheuristic algorithms. Optimization algorithms classified into two broad categories as deterministic and probabilistic algorithms. The content of book elaborates optimization algorithms such as particle swarm optimization, ant colony optimization, whale search algorithm, and cuckoo search algorithm.

✦ Table of Contents

Cover
Front Matter
1. Biomedical Imaging Segmentation and Classification Framework Based on Soft Computing Techniques
2. Optimization Technique Used in Biomedical for Qualitative Sleep Analysis
3. Renewable Energy Optimization Solutions Using Meta-heuristics Methods
4. Stochastic Optimization of Renewable Energy Sources in Distribution Networks
5. Metaheuristic Algorithms for the Classification and Prediction of Skin Lesions: A Comprehensive Review
6. Automatic Prediction of Non-alcoholic Liver Disease Using Deep Learning Models
7. Fuzzy Logic Controller-Based Off-Grid Solar Water Pumping System
8. Renewable Energy Optimization System Using Fuzzy Logic
9. Artificial Intelligence-Based Internet of Things Security
10. Memristors: A Missing Element is a Boon Toward the Development of Neuromorphic Computing and AI
11. Machine Learning and Deep Learning Techniques
12. Classification Models in Education Domain Using PSO, ABC, and A2BC Metaheuristic Algorithm-Based Feature Selection and Optimization
13. Metaheuristic Algorithm’s Role in Medical Care and Diagnostics
14. Biomedical Applications of Chiral Nanoplasmonics