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Modeling and simulating complex busi...

Dikopoulou, Zoumpolia.

Modeling and simulating complex business perceptionsusing graphical models and fuzzy cognitive maps /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modeling and simulating complex business perceptionsby Zoumpolia Dikopoulou.
Reminder of title:	using graphical models and fuzzy cognitive maps /
Author:	Dikopoulou, Zoumpolia.
Published:	Cham :Springer International Publishing :2021.
Description:	xxv, 154 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Fuzzy decision making.
Online resource:	https://doi.org/10.1007/978-3-030-81496-0
ISBN:	9783030814960$q(electronic bk.)

Modeling and simulating complex business perceptionsusing graphical models and fuzzy cognitive maps /
Dikopoulou, Zoumpolia.

Modeling and simulating complex business perceptionsusing graphical models and fuzzy cognitive maps /[electronic resource] :by Zoumpolia Dikopoulou. - Cham :Springer International Publishing :2021. - xxv, 154 p. :ill. (some col.), digital ;24 cm. - Fuzzy management methods,2196-4149. - Fuzzy management methods..

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.

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.

ISBN: 9783030814960$q(electronic bk.)

Standard No.: 10.1007/978-3-030-81496-0doiSubjects--Topical Terms:

346451
Fuzzy decision making.

LC Class. No.: QA279.6 / .D55 2021

Dewey Class. No.: 519.542

Modeling and simulating complex business perceptionsusing graphical models and fuzzy cognitive maps /
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490 1 $a Fuzzy management methods, $x 2196-4149
505 0 $a 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.
520 $a 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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