Optimal Estimation and Precision Analysis of Measuring Data Fusion Model

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Xuanying Zhou
Jiongqi Wang
Zhengming Wang
Zhangming He

Abstract

In the multi-attribute decision making problems, how to effectively extract the decision making rules and rank the schemes are much more important research contents. However, the acquisitions of the decision making rules often are ignored. In view of this, with respect to the problems that there exist a lot of preference information and fuzzy information in the real decision making information system, a novel decision making methodology based on dominance intuitionistic fuzzy rough set is constructed in the paper, and then it is applied to audit risk assessment and risk judgment. Based on the analysis of model and example, the result shows that the proposed model can well realize the extraction of the decision making rules and the ranking of the schemes, and effectively deal with the intuitionistic fuzzy information system with preference information.

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How to Cite
Zhou, X., Wang, J., Wang, Z., & He, Z. (2015). Optimal Estimation and Precision Analysis of Measuring Data Fusion Model. Advances in Systems Science and Applications, 15(3), 254-266. Retrieved from https://ijassa.ipu.ru/index.php/ijassa/article/view/373
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