Analysis of the track and intensity of typhoon"Saola"(2309)based on the Genetic Neural Network Method
Based on a variety of numerical forecast products,this paper analyzes the change characteristics of the typhoon"Saola"and its interaction with the environmental flow field through the comprehensive use of a variety of intelligent computing methods and system dimensionality reduction techniques,and then analyses and study the prediction of the track and intensity of typhoon"Saola"(2309)by using the Guangxi Genetic Neural Network Typhoon Forecasting Method(GXGNNTFM).The results show that the GXGNNTFM has high forecasting accuracy and stable forecasting performance,and has excellent performance in predicting the intensity of typhoon"Saola",but the predicting error of this method in the track forecast is larger than that of the other forecasting models.In the future,for this type of typhoon that rotates in the early stages and steadily moves westward in the late stages,it is necessary to analyze and improve the prediction factors and data mining techniques of the model to improve the accuracy of this method in predicting abnormal typhoon track.
neural network in Guangxityphoon"Saola"track predictionintensity prediction
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