Neural network-based base station coverage abnormality inspection system and method including a neural network learning model, an input data module and a prediction data calculation module

The present invention discloses a neural network learning model, which associates a mass data database with a base station database based on a historical data to model at least one weight and at least one partial weight of a neural network. The model includes an input data module, which collects at least one user device data. The user device data includes at least a longitude and latitude data where the user device is located and a number of a base station with which the base station is connected to the user device; and a prediction data calculation module, which performs calculations on the user device data according to the weight and the partial weight to generate an inspection result of the base station coverage abnormality.