Research on Improvement of Train Curve Fitting Algorithm
LI Weidong
GAO Yingying
Abstract：In order to obtain high efficiency and high precision track curve,it provides accurate spatial analysis means for rail?way operation and maintenance to realize train positioning and operation control. In this paper,the error characteristics of historical positioning data are used to propose an improved logistic regression algorithm model for online learning. It can accelerate the conver?gence by the steepest descent method and fit multiple orbital curve data. It verifies the feasibility of complex conditions such as cross track,parallel orbit,and analyzes the influence of multiple orbital fitting accuracy under different Lambda(learning rate). In this paper,the improved regression model is more accurate than the logic regression fitting algorithm. In the reasonable selection of Lambda(learning rate),it can fit multiple orbital curve data at the same time and ensure the accuracy of fitting degree is over 90%.
Keywords：orbital curve fittinglogistic regressionsteepest descent methodonline learning
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1326-1330,1356 )