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Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science
Paperback
Series: Studies in Computational Intelligence, Book 975
Technology & EngineeringGeneral Computers
ISBN13: 9783030746421
Publisher: Springer Nature
Published: Jun 30 2022
Pages: 393
Weight: 1.29
Height: 0.86 Width: 6.14 Depth: 9.21
Language: English
Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available.
This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.
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