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Journal of Applied Sciences
  Year: 2013 | Volume: 13 | Issue: 16 | Page No.: 3251-3256
DOI: 10.3923/jas.2013.3251.3256
 
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An Integrated RS and ANN Design Method for City’s Industry Development Stage Identification

Wang De-Lu, He Xin and Zhao Shen

Abstract:
In recent years, research about industry development stage identification is taken seriously increasingly and great achievements have been made. Against the background of urban economy, an identifying method of city’s industry development stage is put forward based on integration of Rough Sets (RS) and Artificial Neural Network (ANN). At first, the continuous attribute values are discretized using fuzzy clustering algorithm based on Maximum Discernibility Value (MDV) search method and information entropy. And then the major attributes are reduced by rough sets. At last, the Radial Basis Function (RBF) neural network is trained with training samples and the industry life cycle stages of testing samples are identified. The analysis results taking 669 industries of Dalian city as samples show that the fuzzy clustering algorithm based on MDV and information entropy can improve the discretization performance effectively. Compared with normal fuzzy evaluation method, the predicting precision of integration method is higher and it is an efficient and practical tool to identify development stage of city’s industry.
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How to cite this article:

Wang De-Lu, He Xin and Zhao Shen, 2013. An Integrated RS and ANN Design Method for City’s Industry Development Stage Identification. Journal of Applied Sciences, 13: 3251-3256.

DOI: 10.3923/jas.2013.3251.3256

URL: https://scialert.net/abstract/?doi=jas.2013.3251.3256

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