Typhoon inner core wind speed modeling method by RBFNN and PDE based on infrared cloud image

At present, linear regression model is often used to estimate typhoon inner core wind field. But the fitting effect of typhoon inner core wind speed based on linear regression was bad. Based on infrared satellite cloud image, radial basis function neural network (RBFNN) and partial differential equation(PDE) were used to build a model between typhoon inner core speed and cloud image's gray value. Firstly, typhoon's eye wall was extracted by using PDE which based on geodesic active contour model from the infrared satellite cloud image and the eye wall's space position and brightness are obtained. Then the maximum wind speed near typhoon center which was recorded by typhoon yearbook was used to build a model between typhoon inner core's speed and cloud image's gray value by RBFNN. The experimental results show that the proposed algorithm improves the fitting effect of typhoon inner core's wind speed, and the overall performance of the proposed algorithm is better than tradition method of linear regression.