A Prediction Method of Typhoon Sweeping Range

Abstract

The invention relates to a method for predicting the range of typhoons, which includes: improving the causal entropy theory, adding time series information and global evolution information to make it more suitable for meteorological forecasting, and then establishing typhoon historical data based on the improved causal entropy theory Causal network, and predict the possible disaster-affected cities after the typhoon appears through the convolutional LSTM algorithm. The content of the present invention includes: first calculate the causal entropy of the typhoon intensity between each city through the improved causal entropy theory, and then use the city as a node, and the causal entropy between the two cities is the edge weight to establish a directed network. The predictability of the network is extracted, and the time window is introduced to convert the static network into a time-series network, and the improved convolution LSTM model is used to predict the structure of the network in the future. The invention can predict the cities that may be affected when a typhoon occurs, does not need real-time meteorological data of the typhoon, and effectively solves the problem of predicting the affected cities when the weather observation device is damaged.

Description

technical field [0001] The invention belongs to the field of meteorological forecasting, and relates to a typhoon forecasting method, specifically, a forecasting method for typhoon affected range. Background technique [0002] Landfall typhoons often cause serious disasters. Predicting the path of typhoons as early as possible before landfall has always been the research focus of meteorological forecasting, and strong typhoons are likely to cause inaccurate or impossible meteorological observations. Therefore, when the meteorological conditions cannot be accurately observed, the cities that may be affected by typhoons are meteorological top priority in forecasting. On the one hand, it should be considered that the simple use of historical disaster damage to estimate the possibility of urban disaster damage ignores the problem that different typhoons have different trajectories; on the other hand, the lack of real-time data should be considered, and physical quantities such ...

AI Technical Summary

Problems solved by technology

On the one hand, it should be considered that the simple use of historical disaster damage to estimate the possibility of urban disaster damage ignores the problem that different typhoons have different trajectories; on the other hand, the lack of real-time data should be considered, and physical quantities such as acceleration and heading direction should be used to predict the trajectory of typhoons. lead to less accurate results

Images