The deformation monitoring of foundation pit by back propagation neural network and genetic algorithm and its application in geotechnical engineering.

ABSTRACT: The objective is to improve the prediction accuracy of foundation pit deformation in geotechnical engineering, thereby provide early warning for engineering practice. The digital close-range photogrammetry is used to obtain monitoring data. The error compensation method is used to optimize the center of the monitoring point. Aiming at the limitations of back propagation neural network (BPNN), a genetic algorithm (GA)-optimized BPNN algorithm is proposed. Then, the optimized algorithm is applied to predict the deformation and displacement of foundation pits from three aspects, i.e., simple horizontal displacement, simple longitudinal displacement, and the combination of horizontal and longitudinal displacements. Meanwhile, the time domain, space domain, and time-space domain are used as inp

SUBMITTER: Luo J 

PROVIDER: S-EPMC7329262 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature