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[1]高山卜,钱成文,张沛,等.基于改进的BP神经网络管输能耗预测模型[J].油气储运,2014,33(8):869-872.[doi:10.6047/j.issn.1000-8241.2014.08.014]
　GAO Shanbu,QIAN Chengwen,ZHANG Pei,et al.Prediction model of pipeline energy consumption based on improved BP neural network[J].Oil & Gas Storage and Transportation,2014,33(8):869-872.[doi:10.6047/j.issn.1000-8241.2014.08.014]

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基于改进的BP神经网络管输能耗预测模型

《油气储运》[ISSN:1000-8241/CN:13-1093/TE] 卷: 33 期数: 2014年第8期页码: 869-872 栏目: 出版日期: 2014-08-25

Title:: Prediction model of pipeline energy consumption based on improved BP neural network

作者:: 高山卜¹; 钱成文¹; 张沛²; 张玉志¹; 曾力波¹; 田望¹; 1. 中国石油管道科技研究中心油气管道输送安全国家工程实验室, 河北廊坊065000;
2. 中石油北京天然气管道有限公司, 北京100101

Author(s):: GAO Shanbu¹; QIAN Chengwen¹; ZHANG Pei²; ZHANG Yuzhi¹; ZENG Libo¹; TIAN Wang¹; 1. National Engineering Laboratory of Transportation Safety of Oil&Gas Pipeline, PetroChina Pipeline R&D Center, Langfang, Hebei, 065000;
2. PetroChina Beijing Natural Gas Pipeline Co.Ltd., Beijing, 100101

关键词:: 人工神经网络; BP神经网络; 误差控制; 能耗预测

Keywords:: artificial neural network; BP neural network; error control; energy consumption prediction

分类号:: TE832

DOI:: 10.6047/j.issn.1000-8241.2014.08.014

摘要:: 输油管道能耗指标受多种因素影响，为准确预测输油管道的能耗值，选择具有自组织、自适应能力且能逼近任意非线性连续映射的BP神经网络创建能耗预测模型；为提高模型的泛化能力，在传统的BP神经网络计算过程中加入误差控制公式，最终建立了基于改进的BP神经网络原油管道能耗预测模型。选用某输油管道运行能耗数据作为样本，为提高计算收敛速度和精度，对样本数据进行预处理，对建立的能耗预测模型进行训练和验证，得到该模型的模拟误差在2.77%以内，且模拟值能够真实反映真实值的变化趋势。将该模型推广至某天然气管道进行能耗预测，结果表明：其能够准确预测天然气管输能耗情况，预测误差不超过4.06%。因此，该模型适用于油气管输能耗预测，为管输能耗提供了一种新的预测方法。

Abstract:: Energy consumption of oil pipeline is affected by many factors.To predict the energy consumption accurately, the BP neural network,which is capable of self-organizing,self-adaptation,and approximating any nonlinear continuous mapping,is adopted to build a prediction model.In order to make the model more generalized,the error control formula is added in the computing process with traditional BP neural network.Finally,a prediction model of crude oil pipeline is obtained based on improved BP neural network.This model is applied to the samples of energy consumption taken from a pipeline,which are pre-processed in order to improve the convergence speed and accuracy.The results show that the simulation error of the model is within 2.77%,and the analog value can truly reflect the true value.Then,the model is promoted to a natural gas pipeline,indicating that the model can accurately predict the energy consumption of natural gas pipeline,with error not more than 4.06%.Therefore,this model,as a new method,is applicable to predicting the energy consumption of oil and gas pipelines.

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备注/Memo

收稿日期:2013-8-19;改回日期:2014-5-30。
作者简介:高山卜，助理工程师，1986年生，2012年硕士毕业于西南石油大学油气储运专业，现主要从事油气管道信息与规划研究工作。Tel：0316-2176940，Email：365311351@qq.com

更新日期/Last Update: 1900-01-01