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- W2047642622 abstract "Gasoline blending is an important unit operation in gasoline industry. A good model for the blending system is beneficial for supervision operation, prediction of the gasoline qualities and performing model-based optimal control. Gasoline blending process involves two types of proprieties: static blending and dynamic in the blending tanks. The blending process cannot be modeled exactly, because it does not follow ideal mixing rules in practice. In this paper we propose a hybrid neural network, which uses static and dynamic neural networks to approximate the blending properties. Numerical simulations are provided to illustrate the neuro modeling approach." @default.
- W2047642622 created "2016-06-24" @default.
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- W2047642622 date "2014-07-01" @default.
- W2047642622 modified "2023-09-22" @default.
- W2047642622 title "Hybrid neural networks for gasoline blending system modeling" @default.
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- W2047642622 doi "https://doi.org/10.1109/ijcnn.2014.6889480" @default.
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