Study on Optimum Multi-Parameter Growth Functions of Deformation Prediction for Loess Tunnel Initial Structure

Abstract

Initial structure deformation prediction based on the regression analysis is an important means to evaluate the stability of tunnel, but the commonly used regression functions, such as exponential, logarithmic and hyperbolic function, have disadvantages of low accuracy. Aiming at the drawbacks, 3 kinds of multi-parameter growth functions (Weibull growth function, Richard function and Gompertz growth function) and 3 kinds of commonly used functions (exponential, logarithmic and hyperbolic function) are used to conduct the regression analysis for a loess tunnel’s initial structure in north-west China. Comparison results show that, (1) regressions based on multi-parameter growth functions are far more precise than the commonly used functions, reflecting its superiority in initial structure deformation prediction of the loess tunnel, (2) the more coefficients the function have, the higher the regression correlation is, and (3) the similarity of iterative and error analysis algorithm in different multi-parameter growth functions lays foundations for computer programming realization of regression analysis and model selection automation.