Overview
- Presents solutions of Business Decision Making Problems using data and knowledge
- Introduces soft computing theoretical approaches and applications for Business Analytics (BA)
- Includes chapters with soft computing theoretical approaches development for BA, and soft computing BA applications to important business decision making problems
Part of the book series: Studies in Computational Intelligence (SCI, volume 953)
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Table of contents (23 chapters)
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Decision and Prescriptive Analytics
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Predictive Analytics
Keywords
About this book
Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.
Editors and Affiliations
Bibliographic Information
Book Title: Computational Intelligence for Business Analytics
Editors: Witold Pedrycz, Luis Martínez, Rafael Alejandro Espin-Andrade, Gilberto Rivera, Jorge Marx Gómez
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-73819-8
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-73818-1Published: 27 October 2021
Softcover ISBN: 978-3-030-73821-1Published: 27 October 2022
eBook ISBN: 978-3-030-73819-8Published: 26 October 2021
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: IX, 423
Number of Illustrations: 55 b/w illustrations, 92 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Business Mathematics, Big Data/Analytics