基于新陈代谢GM(1,1)-Markov链模型的有效灌溉面积预测

Effective Irrigated Area Prediction Based on Metabolism GM(1,1)-Markov Chain Model

采用新陈代谢GM(1,1)模型对全国有效灌溉面积的动态变化进行初次拟合和预测,并根据有效灌溉面积时间序列波动的随机性,利用Markov链模型对新陈代谢GM(1,1)模型的残差进行修正,以概率形式确定出未来全国有效灌溉面积的动态变化区间,并依此模型预测未来10年全国有效灌溉面积的发展趋势。结果表明,该模型预测结果准确可靠,可为区域水资源规划管理及农业发展规划决策提供一定的科学依据。

Metabolism GM（1,1） model was used to fit and predict dynamic change of effective irrigated area in China.The residuals of Metabolism GM（1,1） model were revised by the Markov chain model in order to improve the precision of the prediction.Because of the fluctuation of time series,the predicted value for the effective irrigated area was demonstrated with the probability form.And then national effective irrigated area was predicted from 2010 to 2019 based on the established Metabolism GM（1,1）-Markov Chain Model.The results showed that the model was an effective prediction technique to be applied to predict effective irrigated area in the future.