| 基于灰色神经网络的输油管道运行费用预测 |
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| 引用本文： | 李建松,;王惠秋,;王国付. 基于灰色神经网络的输油管道运行费用预测[J]. 管道技术与设备, 2014, 0(4): 10-11 |
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| 作者姓名： | 李建松, 王惠秋, 王国付 |
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| 作者单位： | [1]冀东油田南堡油田作业区,河北唐山063200; [2]辽宁石油化工大学,辽宁抚顺113001 |
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| 摘 要： | 输油管道运行费用的预测在原油运输中有着重要意义,文中将灰色预测模型与神经网络预测模型结合起来,建立灰色神经网络预测模型,对输油管道运行费用进行预测。灰色神经网络预测模型充分发挥了灰色预测模型和神经网络预测模型样本少、计算速度快的优点。计算结果表明：灰色神经网络与EBP神经网络相比,预测模型精度高,计算量小,收敛速度快。
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| 关 键 词： | 灰色预测 神经网络 运行费用 |
Oil Pipe Transportation Expense Prediction Based on the Grey Neural Network |
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| Affiliation: | LI Jian-song ,WANG Hui-qiu ,WANG Guo-fu( 1. Nanpu Production Section of Jidong Oilfield, Tangshan 063200, China; 2. Liaoning Shihua University, Fushun 113001, China) |
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| Abstract: | Oil pipe transportation expense predictions are of significance to crudes transportation. Based on a grey prediction model and a neural network prediction model,a model of grey neural network prediction is built. Grey neural network predictions can help ensure oil pipes to run safely. The grey neural network prediction model makes sufficient use of the advantage of grey prediction and neural network prediction models. Calculation shows that the grey neural network prediction model is of higher prediction precision. It needs fewer calculation times and has a faster rate of convergence than EBP neural network. |
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| Keywords: | grey prediction neural network transportation expense |
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