Prediction Algorithm of GSM-R Field Intensity Coverage Based on GRNN
Ji Guan · Railway Standard Design · 2014
In this paper,the prediction accuracies of field intensity coverage were compared between the Hata modified model and the generalized regression neural network( GRNN) algorithm,and then some simulations were made to analyze the effect of the composition of training set and the smoothing factor on prediction accuracy of GRNN algorithm. Further,some guidelines for choosing the training set and smoothing factor were given. Finally,the paper suggested that: the applicability of GRNN model with different environment can be represented by similarity coefficient of radio propagation environment. The conclusion drawn from the simulation experiment result is that: the greater the similarity coefficient of two propagation environments is,the more accurate in another environment the prediction of GRNN model determined by testing data in one environment will become.