Machine Learning and Metaheuristics: Methods and Analysis (Algorithms for Intelligent Systems) - Softcover

Über die Autorin bzw. den Autor

·     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. 

Essam H. Houssein received his Ph.D. degree in Computer Science (AI). He is an associate professor at the Faculty of Computers and Information, Minia University, Egypt. He is the founder and the chair of the Artificial Intelligence Research (AIR) Group in Egypt. He has more than 200 scientific research papers published in prestigious international journals in the topics for instance meta-heuristics optimization, artificial intelligence, image processing, IoT, and its applications. He serves as a reviewer of more than 100 journals (Elsevier, Springer, IEEE, etc.). His research interests include WSNs, IoT, AI, bioinformatics and biomedical, image processing, data mining, and meta-heuristics optimization techniques.

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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.