Ye Hankun
School of International Trade and Economics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, China
ABSTRACT
BP neural network algorithm has one of the most important algorithms in intelligence field for its powerful nonlinear mapping ability and many other advantages. But BP neural network algorithm has the disadvantages such as low convergence which limits the application of the algorithm. The paper improves the original BP neural network algorithm through Fourier basis function and uses it to evaluate university innovation education. First the disadvantages and its sources of original BP neural network algorithm is analyzed; Second Fourier basis function and BP neural network algorithm are integrated and the calculation flow is redesigned to simplify the algorithm structure and speed up the calculation efficiency of the presented algorithm. Finally data of innovation education from three universities are selected to confirm the performance of the improved BP algorithm and experimental results show that the algorithm can be used practically in evaluating innovation education for different universities and guarantee the evaluation effectiveness and validity.
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How to cite this article
Ye Hankun, 2013. A New BP Neural Network Algorithm and Its Application in University Innovation Education Evaluation. Information Technology Journal, 12: 2790-2793.
DOI: 10.3923/itj.2013.2790.2793
URL: https://scialert.net/abstract/?doi=itj.2013.2790.2793
DOI: 10.3923/itj.2013.2790.2793
URL: https://scialert.net/abstract/?doi=itj.2013.2790.2793
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