Rental price spatial variation prediction method and system based on artificial neural network improved GWR

The invention discloses a house renting price spatial variation prediction method and system based on an artificial neural network improved GWR, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining house renting data from a database, and building a house price model based on the house renting data; establishing a GWR model through the housing price model, and integrating the GWR model into an artificial neural network to construct a prediction model; carrying out model optimization on the prediction model by utilizing a geographical weighted activation function and a gradient descent algorithm; and acquiring real-time house renting data, and inputting the real-time house renting data into the optimized prediction model to obtain a house renting price spatial heterogeneity variation prediction result. According to the method, all characteristics of the GWR are inherited by the AGWNN prediction model, bandwidth optimization is carried out by means of the G