Typhoon disaster assessment method based on deep learning

The invention relates to a typhoon disaster assessment method based on deep learning. According to the method, network real-time comment information is processed by using a deep learning method, and a classification result of typhoon disaster comment information is expressed by adopting interval neutrosophy numbers. Specifically, by taking Heigbi typhoon as an example, the method comprises the following steps: firstly, classifying real-time comment information by using a trained text classification model, then quantizing the comment information into an interval neutrosophy number by taking a classification result as a weight, and finally, sorting the influence degrees of typhoon disasters in each region by adopting a TOPSIS method. The sorting result is used for assisting post-disaster emergency rescue work. According to the method, detailed sensitivity analysis is carried out to determine the optimal parameter setting of the classification model, the method is compared with an existing method from the two as