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2012 (Vol. 4, Issue: 13)
Article Information:

On the Estimate Method of Construction Engineering Cost Based on the RS-GA-NNA Model

Xie Zheng and Mo Lian-Guang
Corresponding Author:  Xie Zheng 

Key words:  Estimation, genetic algorithm, neural network, rough set, , ,
Vol. 4 , (13): 2003-2008
Submitted Accepted Published
March 15, 2012 April 08, 2012 July 01, 2012

Given the low intelligent level and the low accuracy of valuation of civil architecture projects, we put forward in the study a constructional engineering assessment method based on Artificial Intelligence which taking advantage of data-calculation from rough set theory, genetic algorithm and neural network algorithm. First, the rough set theory is used to reduce the discrete attributes to optimize the input variables of BP neural network. And then use the global search feature of genetic algorithm to optimize the initial weight and the threshold value of BP neural network. The new algorithm covers both the global random search capability of genetic algorithm and the learning ability and robustness of neural network, thus the computational speed and accuracy have been more significantly improved than the traditional methods. To empirically analyze a case selected from a city in Hunan Province, the results show that the new algorithm model can rely on the engineering features, assess the construction costs scientifically and objectively and have high practical value.
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  Cite this Reference:
Xie Zheng and Mo Lian-Guang, 2012. On the Estimate Method of Construction Engineering Cost Based on the RS-GA-NNA Model.  Research Journal of Applied Sciences, Engineering and Technology, 4(13): 2003-2008.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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