伊犁河谷伊宁县日降水量值的神经网络预测模型

Neural Network Prediction Model of Daily Precipitation Value in Yining County of Yili Valley

伊犁河谷是新疆重要的农业区,为预防洪水灾害,对降水量进行预测十分必要。本文基于深度学习,对伊宁县构造了BP、RNN、LSTM、GRU 4种不同的神经网络模型,利用该地区2015—2021年的气象数据训练日降水量值预测模型,采用2022年1月1日—5月19日日降水量值对4种模型进行测试评估。结果表明,4种模型中LSTM神经网络模型对日降水量值的预测结果最好,该模型可以作为伊宁县日降水数值的预测模型,其预测的降水量值可作为当地预报洪水灾害的一个重要参考指标,为伊宁地区的防灾减灾提供科学依据。

Since the Yili Valley is an important agricultural area in Xinjiang,it is necessary to forecast the precipitation in order to prevent flood disaster.Based on the deep learning of Yining County,by constructing four neural network models of BP,RNN,LSTM and GRU,in this paper,the daily precipitation value prediction model is trained with the meteorological data from 2015 to 2021,and the daily precipitation value from January 1 to May 19,2022,is used to test and evaluate the four models.The results show that the LSTM neural network model has the best prediction result for the daily precipitation value among the four models.This model can be used as a prediction model for the daily precipitation value in Yining County,and the predicted precipitation value can be used as an important reference index for local flood prediction,and provide scientific basis for disaster prevention and reduction in Yining area.