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| 摘要: |
| 在分析前向BP神经网络基本原理的基础上,对3种混油建立了人工神经网络混油粘度预测模型,该模型结构为1-7-1的三层BP网络模型。运用实测数据对BP网络进行训练和仿真。结果 表明,三种模型预测误差全在2.5%以内,比前苏联学者提出的混油粘度计算公式——克恩达尔-莫恩罗埃公式和兹达诺夫斯基公式更具有计算精度高、适用性强的特点,可完全满足工程实际需要。 |
| 关键词: 管道 BP神经网络 混油粘度 预测模型 |
| DOI： |
| 分类号:TP183 |
| 基金项目:辛石化集团公司项目X504007;江苏省油气储运重点实验室资助ZDK0602004. |
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| Research on the Model of Forecasting the Viscosity of Oil Mixture Based on the BP Neural Network |
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Zhao Huijun Zhang Qingsong Wang Hong et al
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| Abstract: |
| The model of forecasting the viscosity of oil mixture is set up respectively to three different mixtures based on analysis of the basic principle of forward back propagation (BP neural network. The structure of model is 1-7-1 three-layer BP network.. The |
| Key words: pipeline, BP neural network, viscosity of oil mixture, forecasting model |
