2009 Volume 3 Issue 11
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Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.
Citation: Liang Jing, Zhang Yanguo, Meng Aihong, Li Qinghai. Applying neural network to optimize the melting point prediction of simulant solid waste ash[J]. Chinese Journal of Environmental Engineering, 2009, 3(11): 2087-2090.
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Applying neural network to optimize the melting point prediction of simulant solid waste ash

  • 1.

    Key Laboratory for Thermal Science and Power Engineering， Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China

  • Received Date: 20/03/2009
    Accepted Date: 05/05/2008
    Fund Project:
  • The experiment of slag melting point measurement has been done using compounds of SiO2, Al2O3, CaO, Na2CO3, NaCl and Fe2O3, which are mixed to simulate real slag. Then a neural network model is set up to predict the melting point, which is used to direct further experiments and improve the model. This model can predit HT (hemisphere temperature) with an average error of less than 5%.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Applying neural network to optimize the melting point prediction of simulant solid waste ash

  • Received Date: 20/03/2009
  • Accepted Date: 05/05/2008
Fund Project:

Abstract: The experiment of slag melting point measurement has been done using compounds of SiO2, Al2O3, CaO, Na2CO3, NaCl and Fe2O3, which are mixed to simulate real slag. Then a neural network model is set up to predict the melting point, which is used to direct further experiments and improve the model. This model can predit HT (hemisphere temperature) with an average error of less than 5%.

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