Yaochu Jin

(Author)

Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science (2021)Paperback - 2021, 30 June 2022

Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science (2021)
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Part of Series
Studies in Computational Intelligence
Print Length
393 pages
Language
English
Publisher
Springer
Date Published
30 Jun 2022
ISBN-10
3030746429
ISBN-13
9783030746421

Description

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.

Product Details

Authors:
Yaochu JinHanding WangChaoli Sun
Book Edition:
2021
Book Format:
Paperback
Country of Origin:
NL
Date Published:
30 June 2022
Dimensions:
23.39 x 15.6 x 2.18 cm
ISBN-10:
3030746429
ISBN-13:
9783030746421
Language:
English
Location:
Cham
Pages:
393
Publisher:
Weight:
585.13 gm

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