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.
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.
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.
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.
This work is financially supported by National Natural Science Foundation of China under the project of 71601050 and Civil Aviation Administration of China Science Planned Projects under the project of MHRD20150211.
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-04-2018-0045Download as .RIS
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