Journal of Northeastern University Natural Science ›› 2020, Vol. 41 ›› Issue (10): 1483-1490.DOI: 10.12068/j.issn.1005-3026.2020.10.018

• Management Science • Previous Articles     Next Articles

Vector-Type Two-Tuple Semantic Density Weighted Operator and Its Application

YI Ping-tao1,2, WANG Lu1,2, LI Wei-wei1,2   

  1. 1. School of Business Administration, Northeastern University, Shenyang 110167, China; 2. Northeastern Evaluation Center, Shenyang 110167, China.
  • Received:2019-07-01 Revised:2019-07-01 Online:2020-10-15 Published:2020-10-20
  • Contact: YI Ping-tao
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Abstract: Aiming at the problem of multi-attribute decision making, two-tuple semantic information in the form of vector is integrated and an information aggregation method of vector-type two-tuple semantic density weighted averaging (V-TDWA) operator is proposed. Firstly, the basic idea of the vector-type two-tuple semantic weighted operator and its synthetic operators are introduced, and then their properties are analyzed. Secondly, based on the density of information distribution, the clustering problem of the vector-type two-tuple semantic information is discussed, and a clustering method based on vector similarity is given. Based on the clustering group, the maximum entropy value method is used to solve the density weight of different clustering groups. Finally, an example is given to briefly explain the application of the vector-type two-tuple semantic density aggregation operator.

Key words: multi-attribute decision making, two-tuple semantic information, density weighted operator, vector similarity, density weight

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