人工神经网络在含蜡原油黏度预测中的应用

Application of Artificial Neural Network in Viscosity Prediction of Waxy Crude Oil

与传统模型相比,人工神经网络在含蜡原油黏度预测中具有更高的准确性及泛化能力。从原油组分、黏度等多个角度进行分析,结合温度、黏度等因素的影响,建立基于人工神经网络的含蜡原油黏度预测模型,对神经网络结构和参数进行优化,进一步提高模型性能,从人工神经网络预测纳米润滑油黏度与原油黏度预测两方面讨论了其在含蜡原油黏度预测中的应用,以期提供理论参考。

Compared with the traditional model,the artificial neural network has higher accuracy and generalization ability in the viscosity prediction of waxy crude oil.Based on the influence of temperature,and viscosity,etc.,the study establishes the viscosity prediction model of waxy crude oil based on artificial neural network,optimizes the structure and parameters of the neural network,further improves the performance of the model,and discusses the application of artificial neural network in predicting the viscosity of nano-lubricating oil and crude oil.