Estimation of Surface Tension of Molten Silicates Using Neural Network Computation
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概要
- 論文の詳細を見る
Neural network computation was applied to the estimation of surface tension in ternary silicate melts. In addition, the criterion for designing the units in the middle layer of the layer-type neural network computation was discussed. It was found that the Cp-criterion modified by considering the degrees of freedom in the neural network computation was useful for determining the number of units in the middle layer, which gives an optimal estimation. The surface tension calculated by neural network computation using units determined by the Cp-criterion virtually reproduced the experimental data in molten ternary silicates with high precision.
- 社団法人 日本鉄鋼協会の論文
- 2007-08-15
著者
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Kawamoto Masayuki
Corporate R&d Labs. Sumitomo Metal Industries Ltd.
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Holappa Lauri
Laboratory Of Metallurgy Helsinki University Of Technology
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Holappa Lauri
Helsinki University Of Technology Laboratory Of Metallurgy
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Kawamoto Masayuki
Res. And Dev. Laboratories Sumitomo Metal Industries Ltd.
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HANAO Masahito
Research and Development Laboratories, Sumitomo Metal Industries, Ltd.
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Hamalainen Marko
Laboratory Of Material Processing And Powder Metallurgy Helsinki University Of Technology
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Hanao Masahito
Res. And Dev. Laboratories Sumitomo Metal Industries Ltd.
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Hanao Masahito
Corporate Research And Development Laboratories Sumitomo Metal Industries Ltd.
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Tanaka Toshihiro
Division Of Materials And Manufacturing Science Osaka University
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NAKAMOTO Masashi
Laboratory of Metallurgy, Helsinki University of Technology
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Nakamoto Masashi
Division Of Materials And Manufacturing Science Osaka University
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Tanaka Toshihiro
Division Of Materials And Manufacturing Science Graduate School Of Engineering Osaka University
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Nakamoto Masashi
Laboratory Of Metallurgy Helsinki University Of Technology
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Tanaka Toshihiro
Division Of Cardiology Sakakibara Heart Institute
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TANAKA Toshihiro
Division of Materials and Manufacturing Science, Osaka University
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