Thermal Energy Storage, Heat Pump and Thermal Energy Transportation Technologies. Estimation of Quality of Petroleum Products by Neural Networks Models.

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  • 蓄熱・ヒートポンプ・熱輸送　　ニューラルネットワークを用いた石油製品性状推定の検討
  • ニューラルネットワーク オ モチイタ セキユ セイヒン セイジョウ スイテイ

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Abstract

The performance of artificial neural networks on building process models for estimating the quality of petroleum products, research octane number of gasoline, boiling point of gas oil of a topping unit, and flash point of bottom product of a naphtha splitter, are examined in this study. Three types of artificial neural networks models are developed in this study ; back propagation neural network, radial basis function neural network and Wave-net. It is shown that radial basis function neural network model and back propagation neural network model are superior to the other neural networks models on building a steady state model. Wave-net is useful in building a dynamic model for time series data.

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