A TDNN-based precipitation forecasting method for grassland areas in northern China
A North China, forecasting method technology, applied in forecasting, data processing applications, computing and other directions, can solve problems such as low forecasting accuracy, inability to accurately describe the model time relationship, etc., to achieve accurate forecasting, significant environmental and economic strategic value and academic value. Meaning, fill in the effects of inaccurate predictions
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[0033] Now based on the establishment method of the prediction model of monthly average rainfall in the growing season of Hulunbuir Ewenki region from 1961 to 2014, the method for predicting rainfall in the grassland area of northern China based on TDNN proposed by the present invention is described in detail.
[0034] 1. Select the input variables of the prediction model, conduct correlation analysis based on SPSS statistical software, and finally determine the input sequences P(t-1), P(t-2), and P(t-3) corresponding to P(t);
[0035] 2. Obtain the training data and test data of the rainfall TDNN prediction model, according to figure 1 The process of importing the training data into the rainfall TDNN prediction model, and training the rainfall TDNN prediction model;
[0036] 3. Determine the structure of the optimal model, figure 2 As shown, the input variables are determined to be P(t-1), P(t-2), and P(t-3), that is, the rainfall of the previous three years is used as th...
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