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Research On Urban Standard Land Value Evaluation Model Based On Genetic Algorithm Optimized Kriging

Posted on:2006-04-08Degree:MasterType:Thesis
Country:ChinaCandidate:H JieFull Text:PDF
GTID:2179360182467043Subject:Land Resource Management
Abstract/Summary:PDF Full Text Request
Urban standard land price evaluation is the principle and foundation for national macro-control land price and land revenue, it reflects change tendency of land price in land market, and also is the foundation to make further evaluation for land parcel price. Therefore whether the method is scientific and result is accurate or not may affects the reasonable disposition of land resource and the scientific management of land asset. To make sure the reasonability and accuracy in urban standard land price evaluation, it should consider seriously of spatial correlation of price sample, combine closely with new features of urban standard land price evaluation, and also use properly methods for base land value evaluation.This paper firstly makes generally discussion concerning the basic principle of standard land price evaluation. It introduces the basic theory of kriging space analysis and genetic algorithm, then makes description about application of kriging space analysis method in urban standard land price evaluation. It proposes the way of variogram fitting based on genetic algorithm through analyzing deficiency about kriging space analysis in variogram fitting, and also builds a genetic searching model about variogram. This paper takes the example of Wuchang district in Wuhan, verifying optimized kriging method based on genetic algorithm, builds the evaluation model of residential land price, and then makes scientific and rational analysis for the results. So the author finds a new method for urban standard land price evaluation. Finally, in this paper it also takes analysis and prospect toward this new method in urban standard land price evaluation.
Keywords/Search Tags:Base Land Value Evaluation, Kriging Space Analysis, Variogram, Genetic Algorithm, Estimation of Parameters
PDF Full Text Request
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