Metaheuristics for Machine Learning

New Advances and Tools

Mansour Eddaly, Bassem Jarboui, Patrick Siarry (Herausgeber)

Buch | Softcover

223 Seiten

2024
Springer Verlag, Singapore
978-981-19-3890-0 (ISBN)

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Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.

Mansour Eddaly is an assistant professor in the College of Business and Economics at Qassim University (KSA). His current research interests mainly involve combinatorial optimization, metaheuristics, and computational intelligence. Bassem Jarboui is Full Professor of Operational Research at Sfax University, Tunisia, where he also completed his PhD. Currently, he is working at the Higher Colleges of Technology, Abu Dhabi, UAE. He has edited seven books and two special journal issues. He has also organized and chaired five international conferences. He has published over 130 scientific papers, including articles, contributions to edited proceedings, and book chapters. Patrick Siarry received his PhD from the University of Paris 6 in 1986 and his Doctor of Sciences (Habilitation) from the University of Paris 11 in 1994. He first became involved in the development of analogue and digital models of nuclear power plants at Électricité de France (E.D.F.). He has been Professor of Automatics and Informatics since 1995. His main research interest is in the applications of new stochastic global optimization heuristics to various engineering fields.

1. From metaheuristics to automatic programming.- 2. Biclustering Algorithms Based on Metaheuristics: A Review.- 3. A Metaheuristic Perspective on Learning Classifier Systems.- 4. An evolutionary clustering approach using metaheuristics and unsupervised machine learning algorithms for customer segmentation.- 5. Applications of Metaheuristics in Parameter Optimization in Manufacturing Processes and Machine Health Monitoring.- 6. Evolving Machine Learning-based classifiers by metaheuristic approaches for underwater sonar target detection and recognition.- 7. Solving the Quadratic Knapsack Problem using a GRASP algorithm based on a multi-swap local search.- 8. Algorithmic vs Processing Manipulations to Scale Genetic Programming to Big Data Mining.- 9. Dynamic assignment problem of parking slots.

Erscheinungsdatum	15.03.2024
Reihe/Serie	Computational Intelligence Methods and Applications
Zusatzinfo	1 Illustrations, black and white; XV, 223 p. 1 illus.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Artificial Intelligence • Automatic Programming • evolutionary computation • machine learning • Metaheuristics • Swarm intelligence
ISBN-10	981-19-3890-3 / 9811938903
ISBN-13	978-981-19-3890-0 / 9789811938900
Zustand	Neuware