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Research on RBF neural network prediction of oil and gas pipe dent depth

  • Beihang University
  • PetroChina Pipeline Company

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Oil and gas transportation in pipeline plays an important role in the lifeline of national economy, industrial production and daily life. In China, aging phenomenon of oil and natural gas pipeline is widespread in the existing pipeline. Therefore, the safety of the pipeline has been concerned. It is a great significance for forecasting dent depth of transportation pipeline accurately. In this paper, according to the complicated radial displacement and the characteristic of RBF neural network, the model of RBF neural was constructed combining with pipeline dent depth data pipeline. The RBF model was applied to predict dent depth in the pipelines, it was testified that the RBF neural network model has higher prediction accuracy than BP neural network model.

源语言英语
主期刊名AUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems
出版商Institute of Electrical and Electronics Engineers Inc.
335-339
页数5
ISBN(电子版)9781509010875
DOI
出版状态已出版 - 17 11月 2016
活动2016 IEEE/CSAA International Conference on Aircraft Utility Systems, AUS 2016 - Beijing, 中国
期限: 10 10月 201612 10月 2016

出版系列

姓名AUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems

会议

会议2016 IEEE/CSAA International Conference on Aircraft Utility Systems, AUS 2016
国家/地区中国
Beijing
时期10/10/1612/10/16

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