Machine Learning and Metaheuristics: Methods and Analysis

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. 

Biomedical imaging segmentation and classification framework based on soft computing techniques.- On the use of the interactive autodidactic school optimization algorithm for solving real-world engineering optimization problems.- Renewable energy optimization solutions using meta-heuristics methods.- Accelerating the arithmetic optimization algorithm by cuckoo search algorithm for solving global optimization problems.- Metaheuristic algorithms for the classification and prediction of skin lesions: a comprehensive review.- Bayesian consideration for labourer's job performance at home in the COVID-19 pandemic.- Fuzzy logic controller based off-grid solar water pumping system.- An efficient framework for enhancing the performance of biomedical data analysis.- Renewable energy optimization system using fuzzy logic.- An overview of optimization methods in renewable energy technologies.- Use of artificial intelligence and GIS technologies in healthcare services.- ANN and evolution algorithms in ML.- Machine learning and deep learning: essentials and approaches.- Predicting RNA mutations mechanism based on deep neural network.- Comparative analysis for prediction of diseases with feature extraction using machine learning classifiers.- Word sense disambiguation for Hindi language using LSTM neural network technique.- Automatic prediction of non-alcoholic liver disease using deep learning models.- Recent advances for enabling effective human interaction with cognitive robots.

·     Uma N. Dulhare is currently working as a professor and the head Computer Science and Artificial Intelligence Department, Muffakham Jah College of Engineering and Technology, Hyderabad, India. She received her Ph.D. in Computer Science and Engineering from Osmania University, Hyderabad, India. She has published more than 50 research papers in reputed National, International Journals & chapters in the topics machine learning, IoT, image processing. She is the reviewer for Scopus and SCI journals like Springer, Elsevier, IEEE, MDPI, Wiley, etc. Her research interest includes data mining, AI, big data analytics, and machine learning, IoT, cloud computing, biomedical image processing, and soft computing. She is also a pride recipient of Best Computer Science Faculty, Best Academic Researcher, Teaching and Research Excellence, and Outstanding Educator and Scholar award.