Data fusion algorithm based on DS evidence theory and its application in remote maintenance of urban greening
Yijiang Duan, Wei Liu · 2023
Urban greening maintenance is an important work in urban management, but because it is affected by many factors, such as meteorology, soil moisture, light intensity, plant growth state, etc., there are some uncertainties. In this paper, this paper proposes a data fusion algorithm based on DS evidence theory and its application in urban greening conservation and takes soil temperature and humidity as an example to elaborate on how to make accurate water decisions through this method. This method uses DS evidence theory to model and reason about various uncertainty factors to improve the efficiency and accuracy of remote irrigation maintenance in urban greening. At the end of the paper, the practical application effect of this method is proved, and it can provide a new technical means for the remote irrigation and maintenance of urban greening.