Abstract
This paper applied the Data Envelopment Analysis (DEA) method to evaluate the input-output efficiency of constructing the enterprise information. Through projecting the inefficacy DEA unit to make the DEA effective in the unit, the data from projection can be used to train the BP network. In the pure BP network model, some flaws exist in BP network model such as slow speed in convergence and easily plunging into the local minima. On the contrary, artificial immune model has a few advantages such as antibody diversity inheritance mechanism and cell-chosen mechanism, which have been applied in this research. In this research, the BP network has been designed, and the IA-BP network model established. By taking the enterprise information application level, enterprise human resources state and information benefit index as the inputs, and the enterprise investing as the output, this model carries out the network training, until to get the satisfied investment decision method. Basing on this model, the enterprise can realize the maximized return on investment. This model not only constructs a new viable method to effectively use the research data, but also overcomes the drawbacks of non-linear description in the traditional information investment decision. The application results show that the model can satisfy the requirements of enterprise information, and provide the best decision method for enterprises as well.
Project supported by Guangdong Natural Science Foundation (No. 980150)
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© 2005 Springer-Verlag Berlin Heidelberg
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Yan, XK., Yang, HD., Wang, HJ., Deng, FQ. (2005). Research on the Decision Method for Enterprise Information Investment Based on IA-BP Network. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_153
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DOI: https://doi.org/10.1007/11539087_153
Publisher Name: Springer, Berlin, Heidelberg
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