Metaheuristics for Machine Learning: New Advances and Tools (Computational Intelligence Methods and Applications) - Hardcover

 
9789811938870: Metaheuristics for Machine Learning: New Advances and Tools (Computational Intelligence Methods and Applications)
Hardcover
ISBN 10: 9811938873 ISBN 13: 9789811938870
Verlag: Springer, 2023

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

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.


Von der hinteren Coverseite

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.

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Verlag
Springer
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
9811938873
ISBN 13 
9789811938870
Einband
Gebundene Ausgabe
Anzahl der Seiten
238
Herausgeber
Eddaly Mansour, Jarboui Bassem, Siarry Patrick
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

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9789811938894: Metaheuristics for Machine Learning: New Advances and Tools

Vorgestellte Ausgabe

ISBN 10:  981193889X ISBN 13:  9789811938894
Verlag: Springer, 2023
Softcover