Numerical simulation study on big data prediction of pine wood disease

Pine wood nematode disease in China has been growing explosively in recent years, posing a serious threat to plant forest farms and ecological security, and the prevention and control situation is very severe. Based on the investigation of pine wood nematode disease, the environmental impact factors related to the development of the disaster and the disaster situation in recent years were collected and sorted, and the data augmentation of small sample data was carried out through the SMOTE algorithm, so as to generate samples in a new way and increase the diversity of synthetic samples, so as to provide a reliable data basis for the operation of subsequent algorithms and the construction of prediction models. Based on MATLAB software, the BP neural network model in the artificial neural network was used to predict the area of pine wood nematode disease. We need to compare the two models constructed in this paper, one is built using a data that has been studied by numerical simulation, and the other is a model built using a data that has not been processed.