Computational Intelligence for Business Analytics
Published on 26. October 2021
IX, 423 pages
978-3-030-73819-8 (ISBN)
Description
Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
IX, 423 p. 147 illus., 92 illus. in color.
File size
11,54 MB
ISBN-13
978-3-030-73819-8 (9783030738198)
DOI
10.1007/978-3-030-73819-8
Schweitzer Classification
Other editions
Additional editions
Witold Pedrycz | Luis Martínez | Rafael Alejandro Espin-Andrade
Computational Intelligence for Business Analytics
Book
10/2021
Springer
€171.19
Shipment within 7-9 days
Content
Multi-criteria method for evaluating the impact of informal trade on the Mariscal de Puyo market.- Multicriteria Analysis for LPWAN selection for Industry 4.0 based on TOPSIS and a model of Proportionality.- Comprehensive Minimum Cost Models Based on Consensus Measures.- Strategies for the Development and Success of Women Entrepreneurs through SWOT Analysis and Compensatory Fuzzy Logic.- Fuzzy logic-based approaches in supply chain risk management: a review.
