International Journal of Computational Intelligence Systems

<Previous Article In Issue
Next Article In Issue>
Volume 13, Issue 1, 2020, Pages 511 - 523

A Novel Cause-Effect Variable Analysis in Enterprise Architecture by Fuzzy Logic Techniques

Authors
C. Rubio-Manzano1, 2, *, Juan Carlos Díaz1, D. Alfonso-Robaina3, A. Malleuve3, Jesús Medina1
1Department of Mathematics, University Cádiz, Cádiz, Spain
2Department of Information Systems, University of the Bio-Bio, Concepción, Chile
3Universidad Tecnológica de la Habana CUJAE, La Habana, Cuba
*Corresponding author. Email: clrubio@ubiobio.cl
Corresponding Author
C. Rubio-Manzano
Received 14 November 2019, Accepted 7 April 2020, Available Online 2 May 2020.
DOI
10.2991/ijcis.d.200415.001How to use a DOI?
Keywords
Decision-making; Formal analysis of rules; Enterprise architecture; Fuzzy relation equations; Fuzzy sets
Abstract

In this paper, we present a new integration approach for managing Information Technology variables within enterprise architecture in an integrated way. Additionially, a novel method based on fuzzy logic for cause-effect variable analysis is proposed as a useful support decision-making tool for companies in order to know the main actions they must perform for increasing their benefits. This is employed to assess the Integration Management System in Enterprises, based on Enterprise Architecture and Information Technology. We show as fuzzy logic plays an important role in this area due to these variables can be affected for multifactorial elements impregnated with uncertainty. The knowledge given by the experts is translated into dependence rules, which have also been analyzed from a fuzzy point of view using a combination of two fuzzy techniques, namely, fuzzy relation equation theory and fuzzy graph. Firstly, fuzzy dependence rules are computed from fuzzy relation equations and, secondly, an analysis based on incidence subgraph is performed. The result is a strategic plan automatically generated from the data captured of each enterprise in which the most import variables to be improved are detailed.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
13 - 1
Pages
511 - 523
Publication Date
2020/05/02
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.200415.001How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - C. Rubio-Manzano
AU  - Juan Carlos Díaz
AU  - D. Alfonso-Robaina
AU  - A. Malleuve
AU  - Jesús Medina
PY  - 2020
DA  - 2020/05/02
TI  - A Novel Cause-Effect Variable Analysis in Enterprise Architecture by Fuzzy Logic Techniques
JO  - International Journal of Computational Intelligence Systems
SP  - 511
EP  - 523
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200415.001
DO  - 10.2991/ijcis.d.200415.001
ID  - Rubio-Manzano2020
ER  -