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Proceedings Paper

Selection of comparative cases in land appraisal based on cloud model and gray relevancy theory
Author(s): Liu Yang; Yanfang Liu; Wei Liu; Xinying Song; Xiongjie Xu
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Paper Abstract

There is a traditional approach named market comparative method, which is used to appraise land price by putting a focus on comparing cases. A review of the developing history of this method highlights some persistent challenges. In this paper, this existing approach is extended through coupling the cloud model, a data-mining technique, with gray relevancy theory. This approach allows the construction of quantitative measurement according to qualitative concept (attribute), simulating human cognizing process. This novel method admits hierarchical describing and exploration of the relationship and proximity between district factors and individual factors. By 1-D cloud generator, we obtain several rules in terms of linguistic atom which confirm the number of overlap cloud. Each rule corresponds to a rule's rear that achieves uncertainty ratiocination. In order to prove applicability of this method, it is applied to the selection of comparative cases in land appraisal of Wuhan City. Experimental results show most cases can be correctly discriminated and the better comparative cases are acceptable. Compared with other approaches, this method has better performance in land appraisal.

Paper Details

Date Published: 5 November 2008
PDF: 10 pages
Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71442X (5 November 2008); doi: 10.1117/12.812855
Show Author Affiliations
Liu Yang, Wuhan Univ. (China)
Yanfang Liu, Wuhan Univ. (China)
Wei Liu, Wuhan Univ. (China)
Xinying Song, Xinxiang Municipal Bureau of State Land and Resources (China)
Xiongjie Xu, Xinxiang Municipal Bureau of State Land and Resources (China)


Published in SPIE Proceedings Vol. 7144:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Xinhao Wang, Editor(s)

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