E3S Web Conf.
Volume 198, 20202020 10th Chinese Geosynthetics Conference & International Symposium on Civil Engineering and Geosynthetics (ISCEG 2020)
|Number of page(s)||7|
|Section||Exploration and Innovation of Construction Engineering Technology|
|Published online||26 October 2020|
Application of Wavelet Neural Network in Building Settlement Prediction
845 Rue Sherbrooke Ouest, Civil Engineering, McGill University, Montreal, Quebec, H3A 0G4, Canada
Deformation monitoring, as a key link of information construction, runs through the entire process of the building design period, construction period and operation period. At present, more mature static prediction methods include hyperbolic method, power polynomial method and Asaoka method. But these methods have many problems and shortcomings. In this paper, based on the characteristics of building foundation settlement and the methods widely discussed in this field, a wavelet neural network model with self-learning, self-organization and good nonlinear approximation ability is applied to the prediction problem of building settlement. Using comparative analysis and induction method. The 20-phase monitoring data representing the deformation monitoring points of different settlement states of the line tunnel, using the observation data sequence of the first 15 phases respectively to take the cumulative settlement and interval settlement as training samples, through the BP artificial neural network and the improved wavelet neural network, for the last five periods Predict the observed settlement.Through the comparison, it is found that whether the interval settlement or the cumulative settlement is used, the prediction results of the wavelet neural network are basically better than the prediction results of the BP artificial neural network, and the number of trainings is greatly reduced. The adaptive prediction of the wavelet neural network. The ability is particularly obvious, and the prediction accuracy is significantly improved. Therefore, it can be shown that the wavelet neural network is indeed used in the settlement monitoring and forecast of buildings, which can obtain higher prediction accuracy and better prediction effect, and is a prediction method with great development potential.
© The Authors, published by EDP Sciences 2020
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