【摘 要】
：
For the gasoline pipeline blending process,recipe optimization system is greatly dependent on the near-infrared spectroscopy online analyzer,whose spectral model plays an important role in the measure
【机 构】
：
East China University of Science and Technology,China
【出 处】
：
第三届先进计算智能与智能信息学国际研讨会(The Third International Workshop on Adv
论文部分内容阅读
For the gasoline pipeline blending process,recipe optimization system is greatly dependent on the near-infrared spectroscopy online analyzer,whose spectral model plays an important role in the measurement.The spectral models accuracy and adaptability directly affect the applicability of the entire online blending system.This paper studies how to establish model for gasoline octane number for the gasoline pipeline blending process with near-infrared spectroscopy online analyzer.It is proposed using principal component analysis(PCA)together with Artificial Neural Network(ANN)method to establish spectral-model for octane number.Multivariate linear regressions(MLR)and partial least squares(PLS)method have also been used to establish gasoline octane model for comparison purpose.The results show that the model established by PCA and ANN has strong anti-jamming capability and suitable for gasoline online blending application.
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