data fusion, fuzzy sets, Dempster-Shafer (D-S) theory
In cyber-physical systems, multidimensional data fusion is an important method to achieve comprehensive evaluation decisions and reduce data redundancy. In this paper, a data fusion algorithm based on fuzzy set theory and Dempster-Shafer (D-S) evidence theory is proposed to overcome the shortcomings of the existing decision-layer multidimensional data fusion algorithms. The basic probability distribution of evidence is determined based on fuzzy set theory and attribute weights, and the data fusion of attribute evidence is combined with the credibility of sensor nodes in a cyber-physical systems network. Experimental analysis shows that the proposed method has obvious advantages in the degree of the differentiation of the results.
Tsinghua University Press
Guangzhe Zhao, Aiguo Chen, Guangxi Lu et al. Data Fusion Algorithm Based on Fuzzy Sets and D-S Theory of Evidence. Tsinghua Science and Technology 2020, 25(1): 12-19.