辽宁石油化工大学学报2012，Vol.32Issue(4)：52-54,59,4.DOI:10.3696/j.issn.1672-6952.2012.04.014
基于RBF神经网络的输油管道安全停输时间预测
Prediction of Safe Shutdown Time of Oil Pipeline Based on RBF Neural Network
高艳波 1马贵阳 1刘宏宇 2姚尧 1王雷 1代堪亮1
作者信息
- 1. 辽宁石油化工大学石油天然气工程学院,辽宁抚顺113001
- 2. 中国石油天然气管道局国内事业部,河北廊坊065000
- 折叠
摘要
Abstract
Considering the difficulty in the estimation of safe shutdown time of oil pipeline due to the complex safe shutdown of submarine oil pipeline influencing factors, the radial basis function neural network, model was proposed for predicting safe shutdown time of submarine oil pipeline and the various influence factors on safe shutdown of oil pipeline were analyzed. The model was validated on the basis of actual data and the network was trained and the accuracy was verified. The results show that the fitting and simulation precision for training and testing samples is 98. 40% and 97. 33%, respectively. So the safe shutdown time of submarine oil pipeline can be predicted validly, and the important basis of safe transportation of submarine oil pipeline was provided.关键词
径向基函数/安全停输/海底输油管道/预测Key words
Radial basis function/ Safe shutdown/ Submarine oil pipeline/ Prediction分类
能源科技引用本文复制引用
高艳波,马贵阳,刘宏宇,姚尧,王雷,代堪亮..基于RBF神经网络的输油管道安全停输时间预测[J].辽宁石油化工大学学报,2012,32(4):52-54,59,4.
