Modeling of Vehicle Gross Emitter Prediction Based on Remote Sensing Data

Vehicle emission is a major source of air pollution in urban cities. After the introduction of vehicle emissions remote sensing technology, the neural network model for high emitter prediction is made based on the 2004 remote sensing data of Guangzhou. The results show that satisfactory prediction was obtained by reasonable selection of original data for input layer element and algorithm. And the correct rate and the ability of generalization are superior to the traditional model in prediction.