| On Precise Yang Le Inequality and Deficiency Sum |
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| 作者姓名： | JIANG Yun-bo FU De-gang GU Yong-xing |
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| 作者单位： | 1. School of Land Management, HZAU, Wuhan 430070, China; 2. School of Civil Engineering, Southeast University, Nanjing 210096 ,China |
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| 摘 要： | Along with the increase in the number of large-scale construction projects, a series of negative effects concerning various interest-related parts have emerged,which urges a comprehensive and objective evaluation of construction project so as to evaluate its overall satisfaction. In this paper,an evaluation indexes system of construction project satisfaction was advanced,which consists of 19 values coming from all main interest concerning parties, including users, investors, owners, suppliers, government and organizations nearby. A BP neural network evaluation model was built which was self-adaptive, self-organizing and self-study. And this evaluation model was applied to specific project ease. The result showed that this approach can improve the reliability and effectiveness of satisfaction evaluation of the construction project.
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| 关 键 词： | BP neural network construction project satisfaction evaluation |
| 修稿时间： | 2006/12/16 0:00:00 |
On Precise Yang Le Inequality and Deficiency Sum |
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| JIANG Yun-bo,FU De-gang,GU Yong-xing.On Precise Yang Le Inequality and Deficiency Sum[J].Storage & Process,2007(4):125-128. |
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| Authors: | JIANG Yun-bo FU De-gang GU Yong-xing |
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| Institution: | 1. School of Land Management, HZAU, Wuhan 430070, China; 2. School of Civil Engineering, Southeast University, Nanjing 210096 ,China |
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| Abstract: | Along with the increase in the number of large-scale construction projects, a series of negative effects concerning various interest-related parts have emerged,which urges a comprehensive and objective evaluation of construction project so as to evaluate its overall satisfaction. In this paper,an evaluation indexes system of construction project satisfaction was advanced,which consists of 19 values coming from all main interest concerning parties, including users, investors, owners, suppliers, government and organizations nearby. A BP neural network evaluation model was built which was self-adaptive, self-organizing and self-study. And this evaluation model was applied to specific project ease. The result showed that this approach can improve the reliability and effectiveness of satisfaction evaluation of the construction project. |
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| Keywords: | BP neural network construction project satisfaction evaluation |
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