Long term precipitation prediction model establishing method, and long-term precipitation prediction method and apparatus

• Main Authors: Yuan Yang, Mengjie Li, Weiwei Lu, Lili Liang, Kun Liu, Zhiwu Liu, Zhaokai Yin
• Format: Patent
• Language: English
• Published: 02.08.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; MEASURING; METEOROLOGY; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TESTING

A long-term precipitation prediction model establishing method, and a long-term precipitation prediction method and apparatus. The establishing method comprises: acquiring a sample set (step S101); on the basis of a false discovery rate control method for multiple hypothesis testing and a random forest model, screening interpretation variables in the sample set to obtain a prediction factor affecting the precipitation of a corresponding month of the following year (step S102); according to the prediction factor affecting the precipitation amount of the corresponding month of the following year, and the precipitation amount of the corresponding month of the following year, performing random forest modeling, and training to obtain a long-term precipitation prediction model for the precipitation amount of the corresponding month (step S103). By means of the present long-term precipitation prediction model establishing method, and the long-term precipitation prediction method and apparatus, variable screening can be optimized from an experience-dependent method to a data-dependent method, the problem of false positive error rate of the random forest method during empirical screening variables can be improved, and the accuracy and reliability of model prediction can be effectively improved.