Simulation of Mathematical Model to Estimate the Cost of Large-Scale Hydraulic Engineering

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Abstract:

With the rapid development of engineering construction and gradual introduction of the bidding system, project cost estimation model continues to deepen. How to estimate engineering cost fast and accurately become one of the hot topics currently. In this paper, the characteristics of large-scale water project investment risk is combined to establish a neural network model suited for large-scale water project cost, through quantitating the main features of each category of water conservancy and combining neural network model established to quickly estimate water project cost with the toolbox. After engineering examples show that it is a fast and reliable water project cost estimation method.

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3239-3242

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Larranaga P, Etxeberria R, Lozano J, et al. Optimization in continuous domains by learning and simulation of Gaussian networks[C]. Proc of the GECCO-2000 Workshop in Optimization by Building and Using Probabilistic Models. Morgan Kaufmann, 2000: 201-204.

Google Scholar

[2] Figielska E. A genetic algorithm and a simulated annealing algorithm combined with column generation technique for solving the problem of scheduling in the hybrid flowshop with additional resources. Computers and Industrial Engineering, 2009, 56(1): 142−151.

DOI: 10.1016/j.cie.2008.04.008

Google Scholar

[3] Wu H, Wang W P, Wang L, et al. Research on cooperative optimization of improved estimation of distribution algorithm[J]. Computer Engineering and Applications, 2010, 46(26): 28-30.

Google Scholar

[4] Tsutsui S, Pelikan M, Goldberg D E. Probabilistic model-building genetic algorithms using marginal histograms in continuous domain[A]. Proceedings of the International Conference on Knowledge Based Intelligent Information Engineering Systems and Allied Technology[C]. Amsterdam, Netherlands: IOS ress, 2001. 112-121.

Google Scholar

[5] TaoHuaMing. High-rise building foundation mass concrete temperature crack prevention and coping strategies [J]. Bulletin of Science and Technology, 2014. 1: 87-90.

Google Scholar