TIAN Xin, LI Rui-ping, WANG Yan-ming, WANG Si-nan, FAN Lei-lei, FAN Ai-xia
Water Saving Irrigation. 2018, (11):
115-119.
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In order to enable the effective irrigation area of ulan buh develop healthily and understand the development trend of effective irrigation area of ulan buh and irrigation area, this study introduces the regression sliding prediction model of support vector machine,the effective irrigation area data of 2007-2016 was used as a training sample, and the effective irrigation area data for 2017 was used as a test sample,combined with metabolic method, the effective irrigation area of ulan buh irrigation field is predicted. In order to verify the effectiveness and superiority of the model, the Logistic grey prediction model is introduced and compared with support vector machine regression sliding prediction model,the results show that the prediction accuracy of the support vector machine regression sliding model is significantly higher than that of the Logistic grey prediction model. On this basis,the regression model of support vector regression was used to predict the effective irrigated area in each year of Ulanbu and Irrigation from 2018 to 2025 , the effective irrigation area of ulan buh irrigation field in 2022 reached its limit, limit is 53,600 hectares, The effective irrigation area of ulan buh irrigation field in 2017 is 52,440 hectares,is close to its limit, therefore, It can be seen from the predicted results that the growth rate of effective irrigation area in ulan buh irrigation field will start to slow in 2018, and the effective irrigation area will even have negative growth in some years,therefore,it is necessary to analyze the factors affecting the development of effective irrigation area and lay the foundation for healthy development of ulan buh irrigation field.