文章基本信息

标题：DATA MINING TECHNOLOGY IN PREDICTING CULTIVATED LAND DEMAND
本地全文：下载
作者：Liu Yaolin ; Miao Zuohua
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2005
卷号：XXXVI-2/W25
出版社：Copernicus Publications
摘要：Although data mining is relative young technique, it has been used in a wide range of problem domains over the past few decades. In this paper, the authors present a new model to forecast the cultivated land demand adopts the technique of data mining. The new model which is called fuzzy Markov Chain model with weights ameliorate the traditional Time Homogeneous Finite Markov chain model to predict the future value of cultivated land demand in land use planning. The new model applied data mining technique to extract useful information from enormous historical data and then applied fuzzy sequential cluster method to set up the dissimilitude fuzzy clustering sections. The new model regards the standardized self-correlative coefficients as weights based on the special characteristics of correlation among the historical stochastic variables. The transition probabilities matrix of new model was obtained by using fuzzy logic theory and statistical analysis method. The experimental results shown that the ameliorative model combined with technique of data mining is more scientific and practical than traditional predictive models
关键词：Data Mining; Fuzzy Logic Theory; Transition Probability Matrix; Weight