Grey clustering evaluation based on AHP and interval grey number

Abstract

Purpose

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering evaluation problem with IGNs.

Design/methodology/approach

First, the centre-point triangular whitenisation weight function with real numbers is built, and then by using interval mean function, the whitenisation weight function is extended to IGNs. The weights of evaluation indexes are determined by AHP. Finally, this model is used to evaluate the flight safety of a Chinese airline. The results indicate that the model is effective and reasonable.

Findings

When IGN meets certain conditions, the centre-point triangular whitenisation weight function based on IGN is not multiple-cross and it is normative. It provides a certain standard and basis for obtaining the effective evaluation indexes and determining the scientific evaluation of the grey class.

Originality/value

The traditional grey clustering model is extended to the field of IGN. It can make full use of all the information of the IGN, so the result of the evaluation is more objective and reasonable, which provides supports for solving practical problems.

Citation

Chen, K., Chen, P., Yang, L. and Jin, L. (2019), "Grey clustering evaluation based on AHP and interval grey number", International Journal of Intelligent Computing and Cybernetics, Vol. 12 No. 1, pp. 127-137. https://doi.org/10.1108/IJICC-04-2018-0045

Download as .RIS