Temperature is an important meteorological element related to people's livelihood and produc-tion,and the highest and lowest temperature among them attract people's attention,but the relevant re-search is rather little.Based on GRU model,this paper proposes an AI prediction algorithm for high and low temperature in the next 24 hours,and five data processing methods are designed based on the missing data.AI training data sets are made using live and multiple mode data,taking the past 72 hours of live data and the forecast data of the next 24 hours as input.The experiment shows that this method can effectively reduce the prediction error of high and low temperatures.The prediction error of the highest temperature is 1.59°G,and the prediction error of the lowest temperature is 1.19℃.The prediction accuracy is higher than that of the EC model and the forecasters.In particular,the prediction accuracy of the lowest tempera-ture is significantly improved,which has a good guiding significance for the forecasters.
关键词
深度学习/GRU模型/人工智能/高低温预报/数据处理
Key words
deep learning/GRU model/artificial intelligence/high and low temperature forecast/data processing
维普
万方数据