OPERATING METHOD OF DEEP LEARNING BASED CLIMATE CHANGE PREDICTION SYSTEM

摘要

An object of the present invention is to provide an operation method of a deep learning based climate change prediction system capable of predicting more accurate climate change by performing a purification function of missing weather data using a long short-terms memory (LSTM) based purification model. The operation method of the deep learning based climate change prediction system according to one embodiment of the present invention comprises the following steps of: receiving various types of the weather data as weather information; sensing whether there is missed weather data among the weather data to be input; generating refined weather information by applying the weather data predicted by the LSTM networks based purification model to a location of the missed weather data, if there is the missed weather data; and performing climate change prediction based on refined weather information.