Real-time weather prediction algorithm based on LSTM-DNN network model

Abstract

The invention discloses a real-time weather prediction algorithm based on an LSTM-DNN (Long Short Term Memory Network-Deep Neural Network) network model, which is mainly applied to speculation of future weather conditions. The algorithm is divided into two networks, namely a deep neural network and a long-short-term memory network. The deep neural network performs manual classification on input data according to various meteorological elements and current weather conditions, and builds a deep full-connection network for speculating weather conditions according to weather elements to classify the input data. The LSTM network carries out normalization and vectorization processing on input data so as to predict change values of various meteorological elements in a future time period. The output of the LSTM network is used as the input of the trained DNN network, and after the two networks are connected to form the LSTM-DNN network, the future weather condition can be speculated based on the current meteorological elements. According to the invention, the LSTM-DNN network model is applied to the meteorological field, and a real-time weather condition prediction method capable of being realized is provided.

Description

technical field [0001] The invention relates to the fields of meteorology and deep learning, and is a real-time weather prediction algorithm based on an LSTM-DNN network model. Background technique [0002] With the development of the modernization process, more and more emphasis is placed on the results and efficiency of various tasks, and unpredictable weather conditions will have a great impact on people's production and life. The impact of weather changes on traffic is particularly significant. Various extreme weather such as heavy rain and snow not only affect people's travel, but more seriously may cause traffic congestion and even accidents such as car accidents. In addition, severe weather may also cause the suspension of work and production in all walks of life, affecting the advancement of social processes. Due to the impact of global environmental changes, weather forecasting has become more and more complex, and weather conditions will be affected by various sub...

AI Technical Summary

Problems solved by technology

In addition, severe weather may also cause the suspension of work and production in all walks of life, affecting the advancement of social processes

Due to the impact of global environmental changes, weather forecasting has become more and more complex, and weather conditions will be affected by various substances in the atmosphere. The weather may change many times in a day. Monitoring methods are difficult to make timely and accurate judgments on weather changes in a short period of time

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