Modeling and simulating complex business perceptions : using graphical models and fuzzy cognitive aps / Zoumpolia Dikopoulou.
2021
QA279.6
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Title
Modeling and simulating complex business perceptions : using graphical models and fuzzy cognitive aps / Zoumpolia Dikopoulou.
ISBN
9783030814960 (electronic bk.)
3030814963 (electronic bk.)
9783030814953 (print)
3030814955
3030814963 (electronic bk.)
9783030814953 (print)
3030814955
Published
Cham, Switzerland : Springer, 2021.
Language
English
Description
1 online resource (xxv 154 pages) : illustrations (some color)
Item Number
10.1007/978-3-030-81496-0 doi
Call Number
QA279.6
Dewey Decimal Classification
519.5/42
Summary
Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems. This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness. Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 10, 2021).
Series
Fuzzy management methods, 2196-4149
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Table of Contents
Chapter 1. Introduction
Chapter 2. Data Analysis
Chapter 3. Fuzzy Cognitive Maps
Chapter 4. Data Modeling
Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures
Chapter 6. The proposed data-driven glassoFCM method
Chapter 7. Thesis Conclusions.
Chapter 2. Data Analysis
Chapter 3. Fuzzy Cognitive Maps
Chapter 4. Data Modeling
Chapter 5. Network analysis, accuracy and stability of the job-satisfaction structures
Chapter 6. The proposed data-driven glassoFCM method
Chapter 7. Thesis Conclusions.