Li Guoliang
Kunming University of Science and Technology, Kunming, China
ABSTRACT
For improving the wavelet neural network model, the momentum rate was used for dynamic improving the network parameters learning rate and Error entropy function were used for accelerating the network convergence rate. The improved model was applied in a comprehensive energetic evaluation of some listed companies to find out the Chinas building enterprises performance in recent years. The results show that the wavelet neural network as an expert evaluation system could make the evaluation rapidly and efficiently. The wavelet neural network has a unique capacity when a comprehensive dynamic evaluation of the weight accurately calculates is difficult. The results also show that the most corporate performances were low and fluctuation in every year, so the management needed to be improved.
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How to cite this article
Li Guoliang, 2013. An Improved Wavelet Neural Network Model for Evaluation of Corporate Performance. Information Technology Journal, 12: 6756-6762.
DOI: 10.3923/itj.2013.6756.6762
URL: https://scialert.net/abstract/?doi=itj.2013.6756.6762
DOI: 10.3923/itj.2013.6756.6762
URL: https://scialert.net/abstract/?doi=itj.2013.6756.6762
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