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- W2000108117 abstract "This paper deals with a quantitative risk analysis method for V-shaped piers during the construction process, by using the artificial neuron network technique. Regarding the finite element analysis results as a neural network training sample data, an invisible mapping relationship between the basic variables and the structural response is established by means of radial basis function neural networks. Through a numerical simulation based on the principle of Monte Carlo, the structural failure probability of each dangerous section of V-shaped pier during construction is calculated. It is concluded that the structural failure probability of a V-shaped pier’s top segment is higher than that of a root segment under the construction process. Furthermore, suggestion was given in order to reduce potential risks. The method of construction risk analysis based on radial basis function neural network can be widely used as an efficient approach to reliability analysis. It is reasonable and applicable, providing a theoretical basis for risk decision-making during a V-shaped pier’s construction." @default.
- W2000108117 created "2016-06-24" @default.
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- W2000108117 date "2010-07-22" @default.
- W2000108117 modified "2023-10-06" @default.
- W2000108117 title "Risk Analysis of Butterfly Arch Continuous Girder Bridge's V-Shaped Pier during the Construction Process on the Basis of the Technique of Artificial Neural Network" @default.
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- W2000108117 doi "https://doi.org/10.1061/41127(382)367" @default.
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