CAJ | 학술논문

影响耕地面积变化的驱动因子复杂多变，难以确定。为了合理选择耕地面积的驱动因子，提高耕地面积的预测精度，指导耕地资源科学分配利用，通过采用一种基于GS-SVR自变量全组合预测均方误差(Mean Squared Error，MSE)最小原则的方法确定耕地面积的驱动因子；并以湖南省耕地面积变化为例，通过SVR-CAR、LSSVM、BPNN、ARIMA和MLRR等常用的时间序列预测方法来验证所选取驱动因子的有效性。结果表明，湖南省耕地面积变化的最优驱动因子组合为城市化水平和房地产业产值指数，且常用时间序列预测方法采用GS-SVR全组合方式选取的驱动因子组合大幅度提高了耕地面积的预测精度。采用GS-SVR自变量全组合均方误差最小原则的方法选择耕地面积的驱动因子是科学合理的，在耕地面积等时间序列预测领域具有广泛的应用前景。
영향경지면적변화적구동인자복잡다변，난이학정。위료합리선택경지면적적구동인자，제고경지면적적예측정도，지도경지자원과학분배이용，통과채용일충기우GS-SVR자변량전조합예측균방오차(Mean Squared Error，MSE)최소원칙적방법학정경지면적적구동인자；병이호남성경지면적변화위례，통과SVR-CAR、LSSVM、BPNN、ARIMA화MLRR등상용적시간서렬예측방법래험증소선취구동인자적유효성。결과표명，호남성경지면적변화적최우구동인자조합위성시화수평화방지산업산치지수，차상용시간서렬예측방법채용GS-SVR전조합방식선취적구동인자조합대폭도제고료경지면적적예측정도。채용GS-SVR자변량전조합균방오차최소원칙적방법선택경지면적적구동인자시과학합리적，재경지면적등시간서렬예측영역구유엄범적응용전경。
It was complicated and difficult to determine the driving factors which affect changes of cultivated land area. In order to select the effective driving factors and promote the prediction accuracy of cultivated land area, this paper proposed a method to determine the driving factors of cultivated land area relying on the minimum mean squared error (MSE) of prediction value and observed value among all combinations of independent variables based on GS-SVR. Then, taking Hunan province as a case, this paper used several time-series forecasting methods, such as SVR-CAR, LSSVM, BPNN, ARIMA and MLRR to evaluate the performance of the selected driving factors. The results showed that the optimal driving factors for cultivated land changes was the combination of urbanization level and production index of the real estate industry, and with the driving factors selected by GS-SVR, all reference methods greatly improved the prediction accuracy of cultivated land area. The proposed method has an extensive application prospect for predictions involving multidimensional time series data, such as changes of cultivated land area.