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Entropy 2018, 20(7), 523; https://doi.org/10.3390/e20070523

Generalized Grey Target Decision Method for Mixed Attributes Based on Kullback-Leibler Distance

School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Received: 14 May 2018 / Revised: 22 June 2018 / Accepted: 6 July 2018 / Published: 12 July 2018
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Abstract

A novel generalized grey target decision method for mixed attributes based on Kullback-Leibler (K-L) distance is proposed. The proposed approach involves the following steps: first, all indices are converted into index binary connection number vectors; second, the two-tuple (determinacy, uncertainty) numbers originated from index binary connection number vectors are obtained; third, the positive and negative target centers of two-tuple (determinacy, uncertainty) numbers are calculated; then the K-L distances of all alternatives to their positive and negative target centers are integrated by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method; the final decision is based on the integrated value on a bigger the better basis. A case study exemplifies the proposed approach. View Full-Text
Keywords: Kullback-Leibler distance; mixed attributes; generalized grey target decision method; binary connection number; TOPSIS Kullback-Leibler distance; mixed attributes; generalized grey target decision method; binary connection number; TOPSIS
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Ma, J. Generalized Grey Target Decision Method for Mixed Attributes Based on Kullback-Leibler Distance. Entropy 2018, 20, 523.

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