Data-Driven Evolutionary Optimization | Integrating Evolutionary Computation, Machine Learning and Data Science

Yaochu Jin (u. a.)

ISBN 10: 3030746399 / ISBN 13: 9783030746391

Published by Springer, 2021

About this Item

Data-Driven Evolutionary Optimization | Integrating Evolutionary Computation, Machine Learning and Data Science | Yaochu Jin (u. a.) | Buch | xxv | Englisch | 2021 | Springer | EAN 9783030746391 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 119743457

Bibliographic Details

• Title: Data-Driven Evolutionary Optimization | Integrating Evolutionary Computation, Machine Learning and Data Science
• Publisher: Springer
• Publication Date: 2021
• Language: English
• ISBN 10: 3030746399
• ISBN 13: 9783030746391
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 29D millimeters 241 millimeters width by 160 millimeters height by 29 millimeters depth
• Weight: 793 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.