铁道标准设计Issue(2)：106-111,6.DOI:10.13238/j.issn.1004-2954.2014.02.025
基于GRNN的GSM-R场强覆盖预测算法
Prediction Algorithm of GSM-R Field Intensity Coverage Based on GRNN
关捷 1李国宁 1温宇钧2
作者信息
- 1. 兰州交通大学自动化与电气工程学院，兰州 730070
- 2. 中交二公局电务工程公司经营开发部，西安 710065
- 折叠
摘要
Abstract
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.关键词
GSM-R/场强覆盖预测/Hata修正模型/广义回归神经网络/相似系数Key words
GSM-R/prediction of field intensity coverage/Hata modified model/generalized regression neural network/similarity coefficient分类
信息技术与安全科学引用本文复制引用
关捷,李国宁,温宇钧..基于GRNN的GSM-R场强覆盖预测算法[J].铁道标准设计,2014,(2):106-111,6.
