Study on Displacement Prediction Model of Foundation Pit

Abstract:

The prediction model is proposed in this paper to predict the displacement of foundation pit. In the model, genetic algorithms is applied to optimize the node function of the neural network (15 node function coefficients are optimized simultaneously). Next, do the further optimization to the model, and GA-transFcn3 Model is established whose fitness evaluation takes into account the multi-step prediction error. Finally, it is verified that the GA-transFcn3 Model created in this article has the desirable prediction accuracy through engineering examples. The establishment of GA-transFcn3 Model can provide researchers and engineers with ideas and methods for the displacement prediction of foundation pit, and can be popularized and applied in practical projects.

• Periodical: Advanced Materials Research (Volumes 834-836)
• Pages: 679-682
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.834-836.679
• Online since: October 2013
• Authors: Qiang Song, Jun Jian Zhang, Yun Sheng Liu
• Keywords: Foundation Pit, Genetic Algorithm (GA), Neural Network (NN), Prediction Model

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