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Computational intelligence for busin...
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Pedrycz, Witold.
Computational intelligence for business analytics
Record Type:
Electronic resources : Monograph/item
Title/Author:
Computational intelligence for business analyticsedited by Witold Pedrycz ... [et al.].
other author:
Pedrycz, Witold.
Published:
Cham :Springer International Publishing :2021.
Description:
ix, 423 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Computational intelligence.
Online resource:
https://doi.org/10.1007/978-3-030-73819-8
ISBN:
9783030738198$q(electronic bk.)
Computational intelligence for business analytics
Computational intelligence for business analytics
[electronic resource] /edited by Witold Pedrycz ... [et al.]. - Cham :Springer International Publishing :2021. - ix, 423 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 9531860-9503 ;. - Studies in computational intelligence ;v. 216..
Multi-criteria method for evaluating the impact of informal trade on the Mariscal de Puyo market -- Multicriteria Analysis for LPWAN selection for Industry 4.0 based on TOPSIS and a model of Proportionality -- Comprehensive Minimum Cost Models Based on Consensus Measures -- Strategies for the Development and Success of Women Entrepreneurs through SWOT Analysis and Compensatory Fuzzy Logic -- Fuzzy logic-based approaches in supply chain risk management: a review.
Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments. Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.
ISBN: 9783030738198$q(electronic bk.)
Standard No.: 10.1007/978-3-030-73819-8doiSubjects--Topical Terms:
210824
Computational intelligence.
LC Class. No.: Q342 / .C66 2021
Dewey Class. No.: 006.3
Computational intelligence for business analytics
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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.
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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.
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Intelligent Technologies and Robotics (SpringerNature-42732)
based on 0 review(s)
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1圖書
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EB Q342 .C738 2021 2021
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https://doi.org/10.1007/978-3-030-73819-8
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