Abstract: Disclosed is a method for distinguishing sunny-rainy weather based on time division long-term evolution network, including the following steps: acquiring sunny-rainy feature by extracting communication measurement statistics of time division long-term evolution network base stations in a certain area; establishing a training set according to that observation result of multiple statistical periods, multiple base stations and multiple rain gauges in the region; establishing a sunny-rainy discrimination model combined with machine learning binary classification algorithm, so as to realize the identification of rainfall events covered by a single base station; calculating the reliability of rainfall events at specific locations based on the comprehensive judgment results of multiple base stations.

Abstract: Disclosed is a method for distinguishing sunny-rainy weather based on time division long-term evolution network, including the following steps: acquiring sunny-rainy feature by extracting communication measurement statistics of time division long-term evolution network base stations in a certain area; establishing a training set according to that observation result of multiple statistical periods, multiple base stations and multiple rain gauges in the region; establishing a sunny-rainy discrimination model combined with machine learning binary classification algorithm, so as to realize the identification of rainfall events covered by a single base station; calculating the reliability of rainfall events at specific locations based on the comprehensive judgment results of multiple base stations.