Abstract
The construction and investment on infrastructure projects are becoming hotter all around China in the new century. The infrastructure projects of China are showing some unbalance while they promote the regional social and economic development and create excellent benefits for economic development. This paper tried to give out a guide of model and practice about the infrastructure projects investment departure based on neural network. Fist, this paper defined the six early warning indexes—the cost performance index, the schedule performance index, the investment variance, the schedule variance, the risk rate of investment variance and the risk rate of schedule variance. Then, input the historical data of multiple stages to the pre-learning neural network model, we could get the deviation degree of investment in infrastructure projects. Data examples showed that the model was valid.
The work described in this paper has been supported by the education department of Sichuan Province under the grant No. 12ZB139
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Wang, L. (2014). Research of the Investment Departure Early Warning Model of Infrastructure Projects Based on BP Neural Network. In: Yang, D., Qian, Y. (eds) Proceedings of the 18th International Symposium on Advancement of Construction Management and Real Estate. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44916-1_47
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DOI: https://doi.org/10.1007/978-3-642-44916-1_47
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