A settlement prediction model of high-speed railway pier based on GA-BP-MC neural network

doi:10.13474/j.cnki.11-2246.2019.0217

Abstract

Abstract: A genetic BP neural network prediction model (GA-BP-MC) based on Markov chain modification is proposed. The weights and thresholds of BP neural network are initialized by the global optimization ability of genetic algorithm, and the prediction model of GA-BP neural network is established preliminarily. The predictive value of model is modified by the invalidity of Markov chain to form a high precision deformation prediction model of GA-BP-MC neural network. Combined with the settlement data of high-speed railway piers, and compared with the BP neural network and GA-BP neural network prediction models respectively, the results show that the accuracy of the prediction model is highest.

Key words: Markov chain, genetic algorithm, BP neural network, high-speed railway pier, settlement prediction

CLC Number:

P258

FENG Shaoquan, HUA Xianghong, TAO Wuyong, XUAN Wei, WU Wei, XU Dong. A settlement prediction model of high-speed railway pier based on GA-BP-MC neural network[J]. 测绘通报, 2019, 0(7): 50-53,82.

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