Abstract
Aiming at the difficulty of noise estimation and outlier estimation in data fusion, a fuzzy theory data fusion algorithm based on confidence distance is proposed and its application in sensor monitoring is studied. Firstly, according to the characteristics of sensor monitoring values, the characteristics of traditional fuzzy theory data fusion methods are analyzed. Secondly, the confidence distance is used to describe the fuzzy proximity between the data, and the erroneous data is eliminated. Finally, the data is merged by proximity to get the result of the fusion. Experiments show that the difference of the fusion value based on the confidence distance is small, and the fusion result is close to the actual state of the measured object.
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