Application of Radial Basis Function Neural Network on the Prediction of Urban Built-Up Area

Li Hua Chen; Yu Chen Wang

doi:10.4028/www.scientific.net/AMM.556-562.5308

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Application of Radial Basis Function Neural...

Application of Radial Basis Function Neural Network on the Prediction of Urban Built-Up Area

Abstract:

The study on the prediction of urban built-up area is the basic issue in urban planning. This paper takes the prediction of urban built-up area of Hefei city as an example, building a factor system that affects built-up area from the economic, social and environmental dimensions. Then, the paper establishes a quantitative prediction model based on the Radial Basis Function neural network. As a comparison, the paper also uses the Back Propagation neural network to predict. The results show that the Radial Basis Function neural network prediction has a higher accuracy and the prediction result is more reasonable and reliable.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

5308-5311

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.5308

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Online since:

May 2014

Authors:

Li Hua Chen*, Yu Chen Wang

Keywords:

Area, Prediction, Radial Basis Function Neural Network, Urban Built-Up

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* - Corresponding Author

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