A risk assessment method based on Pythagorean fuzzy set and artificial-neuron-like evaluation node

Article type: Research Article

Authors: Rodríguez, Antonio^{; *}

Affiliations: Ingenierías TIC, Escuela PolitécnicaSuperior, Universidad Alfonso X El Sabio, Madrid, Spain

Correspondence: [*] Corresponding author. Antonio Rodríguez, Ingenierías TIC, Escuela Politécnica Superior, Universidad Alfonso X El Sabio, Villanueva de la Cañada, 28691 Madrid, Spain. Tel.: +34 686403654. E-mail: [email protected].

Abstract: Taking concepts from supply management, we developed a specification-assessment-compliance approach to obtain a transparent multi-criteria decision-making method. We designed an artificial-neuron-like node that allows the implementation of networks to represent hierarchies of evaluation criteria. A new graphical model based on functions in the unit segment uses the concept of Pythagorean fuzzy set (PFS). The specification PFSs’ entropies modulate the widths of one-sided triangular fuzzy numbers (TFNs) with positive slopes that become the evaluation nodes’ activation functions. All the specifications refer to the same point to facilitate the evaluation and ensure coherence. One-sided TFNs with negative slopes biunivocally represent the assessment PFSs at the input layer of the network. A risk case study on the options for the outsourcing of an information technology development project shows the proposed method’s implementation. We compare the results with those of the application of two other previous methods.

Keywords: Multi-criteria decision-making, Pythagorean fuzzy set, triangular fuzzy number, artificial neuron, information entropy

DOI: 10.3233/JIFS-210029

Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 4097-4108, 2021