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门限自回归模型及其在耕地总量预测中的应用
引用本文:胡华科. 门限自回归模型及其在耕地总量预测中的应用[J]. 安徽农业科学, 2007, 35(11): 3322-3323. DOI: 10.3969/j.issn.0517-6611.2007.11.096
作者姓名:胡华科
作者单位:嘉应学院地理系,广东梅州,514015;中山大学地理科学与规划学院,广东广州,510275
基金项目:广东省自然科学基金项目(5008167),嘉应学院重点扶持学科资助项目(302E18)
摘    要:利用梅州市55年来长时序耕地总量统计资料,引入门限自回归模型对耕地面积进行了预测,并和马尔可夫模型预测结果进行了比较.结果表明,通过门限值的控制作用,门限自回归模型有效地利用时序数据隐含的时序分段相依性这一重要信息,限制了模型误差,从而保证了预测性能的稳健性,有很高的短中期预测精度.

关 键 词:耕地总量预测  马尔可夫模型  门限自回归模型
文章编号:0517-6611(2007)11-03322-02
收稿时间:2007-01-19
修稿时间:2007-01-19

Threshold Auto-regressive Model and its Application in Gross Arable Land Prediction
HU Hua-ke. Threshold Auto-regressive Model and its Application in Gross Arable Land Prediction[J]. Journal of Anhui Agricultural Sciences, 2007, 35(11): 3322-3323. DOI: 10.3969/j.issn.0517-6611.2007.11.096
Authors:HU Hua-ke
Affiliation:Department of Geography, Jiaying University, Meizhou, Guangdong 514015
Abstract:Long time sequence material of gross arable land in recent 55 years in Meizhou City was used to predict gross arable land by applying Threshold Auto-regressive(TAR) model.And its result was compared with that of Markov model.The result of the calculation showed that the scheme was practical and efficient.TAR model could effectively utilize the important information of the interdependence between section and time series dates,reduce model errors and ensure good stability and accuracy of the forecasting model.
Keywords:Gross arable land prediction  Markov model  Threshold Auto-regressive model
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