GA-NN Monitoring Model and its Application on Surface Settlement

Abstract:

Combining the advantages of basic genetic algorithm and neural network, analyze and set up GA & NN genetic neural network, explore and study the algorithm. The efficiency and effectiveness of this hybrid training has been significantly improved comparing with the single genetic evolution or BP training method, its versatility is better. The model is applied to predict the deformation of shield tunnel excavation. According to the effects of measured influence factors under construction, it can make the appropriate forecast to the surface settlement which is better than the conventional regression model. It shows that neural networks in the ground during tunneling shield analysis and prediction of settlement is practical and adaptable.

• Periodical: Advanced Materials Research (Volume 505)
• Pages: 453-457
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.505.453
• Online since: April 2012
• Authors: Tie Sheng Wang, Hai Yan Li, Bing Zhang, Kai Feng Ma
• Keywords: Deformation Prediction, Genetic Algorithm (GA), Neural Network (NN), Surface Subsidence

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