The Establishment of Land Appraisal Model in Xiamen Based on BP Neural Network

Abstract:

Establish the land evaluation model of Xiamen by means of BP neural network theory, taking 2007-2009 land evaluation cases of Xiamen as examples. Through statistical analysis, we find that the neural network which has 9 net work hidden layer nodes and 19% of maximal error index is more suitable for Xiamen land price assessment than others. Empirical analysis shows that the model has a good generalization ability, which can be used for land evaluation practices. The results indicates that the properties of autonomous learning of BP network can reduce the subjective factors of appraiser in land evaluation , also, the network has the advantage of simple and quick calculation.

• Periodical: Advanced Materials Research (Volumes 518-523)
• Pages: 6084-6087
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.518-523.6084
• Online since: May 2012
• Authors: Qing Ye, Ya Yi Su, Fei Chen
• Keywords: BP Neural Network (BPNN), Generalization Ability, Influence Factor, Land Evaluation Model, Quantitative Standard

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