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Proceedings Paper

A data mining approach for prediction of cultivated land demand in land use planning
Author(s): Yaolin Liu; Zuohua Miao; Wenfei Chen
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Paper Abstract

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.

Paper Details

Date Published: 2 December 2005
PDF: 9 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604537 (2 December 2005); doi: 10.1117/12.651854
Show Author Affiliations
Yaolin Liu, Wuhan Univ. (China)
Zuohua Miao, Wuhan Univ. (China)
Wenfei Chen, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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