改进马尔可夫链耕地需求量预测模型的应用  

Research on Cultivated Land Demand Model Based on Improved Markov Chain

作　　者：韩素芳[1] 

机构地区：[1]云南民族大学经济学院,昆明650000

出　　处：《红河学院学报》2011年第6期81-84,共4页Journal of Honghe University

基　　金：国家"973"基金项目(2006CB100206);云南省十一五科技重点攻关项目(2010NG0011)

摘　　要：文章以耕地利用动态度为度量,利用模糊有序聚类方法将耕地需求量划分为不同的状态区间,并建立马尔可夫链状态转移概率矩阵,以规范化的各阶自相关系数为权重改进传统的马尔可夫链预测模型,用改进后的模型对土地利用规划中耕地需求量进行预测。实验结果表明,改进后的方法预测结果与实际情况吻合,具科学性和实用性。Based on cultivated land use dynamic attitude for measurement, the author uses the fuzzy orderly clustering method to divide the cultivated land demand into different state intervals, and established Markov chain transfer matrix, with standardized autocorrelation coefficient as weights to improve traditional markov chain prediction model, and use the improved model to forecast the demand of cultivated land in land use planning. Experimental results show that the improved method forecasting results is identical with the practical situation, and is scientific and practical.

关 键 词：模糊有序聚类 马尔可夫链 耕地需求量 预测 

分 类 号：O159[理学—数学]