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Article

A Methodology for Redesigning Networks by Using Markov Random Fields

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Department of Applied Mathematics, University of Granada, 18071 Granada, Spain
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Department of Computer Architecture and Computer Technology, University of Granada, 18071 Granada, Spain
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Department of Social Psychology, University of Granada, 18071 Granada, Spain
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Institute of Artificial Intelligence, De Montfort University, Leicester LE1 9BH, UK
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Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Vassilis C. Gerogiannis
Mathematics 2021, 9(12), 1389; https://doi.org/10.3390/math9121389
Received: 10 May 2021 / Revised: 8 June 2021 / Accepted: 10 June 2021 / Published: 15 June 2021
(This article belongs to the Special Issue Group Decision Making Based on Artificial Intelligence)
Standard methodologies for redesigning physical networks rely on Geographic Information Systems (GIS), which strongly depend on local demographic specifications. The absence of a universal definition of demography makes its use for cross-border purposes much more difficult. This paper presents a Decision Making Model (DMM) for redesigning networks that works without geographical constraints. There are multiple advantages of this approach: on one hand, it can be used in any country of the world; on the other hand, the absence of geographical constraints widens the application scope of our approach, meaning that it can be successfully implemented either in physical (ATM networks) or non-physical networks such as in group decision making, social networks, e-commerce, e-governance and all fields in which user groups make decisions collectively. Case studies involving both types of situations are conducted in order to illustrate the methodology. The model has been designed under a data reduction strategy in order to improve application performance. View Full-Text
Keywords: universal decision making model; redesigning networks; Markov random fields universal decision making model; redesigning networks; Markov random fields
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MDPI and ACS Style

García Cabello, J.; Castillo, P.A.; Aguilar-Luzon, M.-d.-C.; Chiclana, F.; Herrera-Viedma, E. A Methodology for Redesigning Networks by Using Markov Random Fields. Mathematics 2021, 9, 1389. https://doi.org/10.3390/math9121389

AMA Style

García Cabello J, Castillo PA, Aguilar-Luzon M-d-C, Chiclana F, Herrera-Viedma E. A Methodology for Redesigning Networks by Using Markov Random Fields. Mathematics. 2021; 9(12):1389. https://doi.org/10.3390/math9121389

Chicago/Turabian Style

García Cabello, Julia, Pedro A. Castillo, Maria-del-Carmen Aguilar-Luzon, Francisco Chiclana, and Enrique Herrera-Viedma. 2021. "A Methodology for Redesigning Networks by Using Markov Random Fields" Mathematics 9, no. 12: 1389. https://doi.org/10.3390/math9121389

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