Abstract: Based on the structure and function of biological neural network,artificial neural network(ANN) can perform distributed storage and parallel processing of data.Self-organizing feature mapping model(SOM) and probabilistic neural network(PNN) are commonly used models in ANN algorithms.Based on the respective characteristics of two mo-dels,the two were connected in series.SOM uses a two-dimensional topology consisting of two layers of neurons to obtain and predict the data.The PNN model converts the output of the SOM and directly outputs the final classification result of the model.The algorithm based on this model can improve the operation speed and remove the interference of noise samples,which greatly improves the accuracy of the model.At present,the Beijing-Tianjin-Hebei regional environment has fallen into a higher risk state.Taking the regional SO₂ concentration prediction as an example,the SOM-PNN model is used to obtain the visual output of the influence mechanism of urban factors on SO₂ concentration and the high-precision prediction of regional environment,which further verifies the feasibility and effectiveness of the proposed model.

Key words: Neural network, Risk prediction, SOM-PNN, Urban environmental