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

机译:RBF神经网络预测油气管道凹陷深度的研究

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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.
机译:管道中的油气运输在国民经济,工业生产和日常生活的生命线中起着重要作用。在中国,石油和天然气管道的老化现象在现有管道中普遍存在。因此,一直在关注管道的安全性。对于准确预测输送管道的凹痕深度具有重要意义。本文针对复杂的径向位移和RBF神经网络的特点,结合管线凹痕深度数据管线,构造了RBF神经网络模型。应用RBF模型预测管道的凹痕深度,证明了RBF神经网络模型比BP神经网络模型具有更高的预测精度。

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