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- W2377068017 abstract "Guangzhou underground railway project is one of the most signifi-cantly important infrastructure projects in the nation. For such kind of substan-tial and complex project, it is necessary to have a proven and reliable publicbidding evaluation system. According to the evaluation data of practical bid-ding engineering in Guangzhou Underground Railway, this paper suggests toemploy Artificial Neural Network (ANN) to set up the comprehensive evalua-tion model for the bidding of underground railway projects. The Back Propaga-tion (BP) neuron networks, which have strong self-learning and self-adaptiveability, can be used to approach the complex nonlinear dynamic functions withhigh precision. After network training, the module based on BP networks cansuccessfully quantify the subjective and qualitative technical evaluation indi-ces with satisfying evaluation results. The module can be more precise byaccumulating more samples so it can be adopted by the bidding project ofunderground railway and similar construction projects." @default.
- W2377068017 created "2016-06-24" @default.
- W2377068017 creator A5078143614 @default.
- W2377068017 date "2003-01-01" @default.
- W2377068017 modified "2023-09-23" @default.
- W2377068017 title "A Synthetic Evaluation Module of Public Bidding in Underground Railway Projects Based onArtificial Neural Networks (ANN)" @default.
- W2377068017 hasPublicationYear "2003" @default.
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