AIJul 17, 2012

Hybrid Grey Interval Relation Decision-Making in Artistic Talent Evaluation of Player

arXiv:1207.3855v14 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental improvement for domain-specific decision-making in artistic talent evaluation, with limited broader impact.

The paper tackles the problem of evaluating artistic talent in Kayagum players by proposing a hybrid grey interval relation TOPSIS method that handles uncertain attribute weights and values as interval grey numbers, demonstrating its practicability through a case study.

This paper proposes a grey interval relation TOPSIS method for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. In this paper, all of the subjective and objective weights are obtained by interval grey number and decision-making is based on four methods such as the relative approach degree of grey TOPSIS, the relative approach degree of grey incidence and the relative approach degree method using the maximum entropy estimation using 2-dimensional Euclidean distance. A multiple attribute decision-making example for evaluation of artistic talent of Kayagum (stringed Korean harp) players is given to show practicability of the proposed approach.

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