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Research on the Decision Method for Enterprise Information Investment Based on IA-BP Network

机译:基于IA-BP网络的企业信息投资决策方法研究

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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.
机译:本文应用数据包络分析(DEA)方法评估了构建企业信息的投入产出效率。通过投影无效的DEA单元以使DEA在该单元中有效,可以将来自投影的数据用于训练BP网络。在纯BP网络模型中,BP网络模型存在一些缺陷,例如收敛速度慢和容易陷入局部极小值。相反,人工免疫模型具有抗体多样性遗传机制和细胞选择机制等优点,已在本研究中得到应用。在这项研究中,已经设计了BP网络,并建立了IA-BP网络模型。该模型以企业信息化应用水平,企业人力资源状况和信息效益指标为输入,以企业投资为输出,进行网络培训,直至获得满意的投资决策方法。在此模型的基础上,企业可以实现最大的投资回报。该模型不仅构建了一种有效利用研究数据的新方法,而且克服了传统信息投资决策中非线性描述的弊端。应用结果表明,该模型能够满足企业信息化需求,也为企业提供了最佳决策方法。

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