Stationary simulation of the gas pipeline using neural networks - Case study of Vojvodina

被引：0
|
作者：
Petrovacki, Nebojsa [1 ]
机构：
[1] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92506 USA
来源：
WMSCI 2006: 10TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL III, PROCEEDINGS | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we discuss the utilization of neural networks in the problem of stationary simulation of a real gas transmission pipeline of Serbian Province of Vojvodina. Firstly, we explain the motivation for this paper and then we provide the basic background of the problem of stationary simulation of the real gas pipeline. Then we implement the feed-forward back-propagation algorithm so that we can train a neural network to produce appropriate pressures at the nodes of the gas pipeline. We observe very good matching of the results of such simulation and real-He measurements provided by the public utility company.
引用
收藏
页码：139 / 143
页数：5
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