引用本文: 苗作华, 刘耀林, 王海军. 耕地需求量预测的加权模糊-马尔可夫链模型[J]. 武汉大学学报 ( 信息科学版), 2005, 30(4): 305-308.
MIAO Zuohua, LIU Yaolin, WANG Haijun. Fuzzy-Markov Chain Model with Weights for Prediction of Cultivated Land Demand[J]. Geomatics and Information Science of Wuhan University, 2005, 30(4): 305-308.
 Citation: MIAO Zuohua, LIU Yaolin, WANG Haijun. Fuzzy-Markov Chain Model with Weights for Prediction of Cultivated Land Demand[J]. Geomatics and Information Science of Wuhan University, 2005, 30(4): 305-308.

## Fuzzy-Markov Chain Model with Weights for Prediction of Cultivated Land Demand

• 摘要: 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模糊状态区间,利用模糊集理论构建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,改进后的方法较传统的预测方法更具科学性和实用性

Abstract: This paper presents a new model called fuzzy-Markov chain model with weights to predict the future value of cultivated land demand in land use planning. The new model ameliorates the traditional time homogeneous finite Markov chain model by adopting fuzzy logic theory. The new model applies fuzzy sequential cluster method to set up the dissimilitude fuzzy clustering sections based on land use trend coefficients. Standardized self-correlative coefficients based on the special characteristics of correlation among the historical stochastic variables are regarded as weights. And the transition probabilities matrix of the new model is obtained by using the fuzzy logic theory and statistical analysis method. The experimental results show that the ameliorative model adopted fuzzy logical theory is more scientific and practical than the traditional predictive model.

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