Abstract
A appraisal model based on the integration of principal component analysis (PCA) and back propagation (BP) neural network is put forward for appraising the real estate project. Firstly, principal component analysis (PCA) is used to reduce the evaluation index dimensions. And then, back propagation (BP) neural network is used to appraise the real estate projects. In order to grasp this appraisal model better, finally, the paper provides a case to demonstrate the application of this model in appraising the real estate project. The case has shown that the model applied to appraise the real estate project is feasible and reliable.
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Wang, X.Q., Yu, G.: Study of construction project bidding based on the BP neural network improved by GA. China Civil Engineering Journal 40(7), 93–98 (2007)
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© 2011 Springer-Verlag Berlin Heidelberg
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Zhao, H. (2011). The Appraisal Model of Real Estate Project Based on PCA and BP Neural Network. In: Shen, G., Huang, X. (eds) Advanced Research on Computer Science and Information Engineering. CSIE 2011. Communications in Computer and Information Science, vol 152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21402-8_51
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DOI: https://doi.org/10.1007/978-3-642-21402-8_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21401-1
Online ISBN: 978-3-642-21402-8
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