| 用自组织人工神经网络研究黄土孔隙性分类判别 |
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| 引用本文： | 蔡煜东,杨兵.用自组织人工神经网络研究黄土孔隙性分类判别[J].干旱区研究,1994,11(4):32-37. |
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| 作者姓名： | 蔡煜东 杨兵 |
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| 作者单位： | 中国科学院上海冶金研究所 |
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| 摘 要： | 本文运用三维Ｔ．Ｋｏｈｏｎｅｎ自组织人工神经网络，对洛川黄土孔隙性的实例数据进行了分析，建立了洛川黄土孔隙性预测的计算机智能专家系统。结果表明，神经网络方法性能良好，可望成为黄土孔隙性分类判别的有效辅助手段。
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| 关 键 词： | 微孔隙定量 洛川 黄土 神经网络 孔隙性 |
Studies on the Differentiation of Loess Porosity Classification by the Method of Self-organizationalArtificial Nerve Network |
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| Cat Yidong,Yang Bing,Tang Junbiao.Studies on the Differentiation of Loess Porosity Classification by the Method of Self-organizationalArtificial Nerve Network[J].Arid Zone Research,1994,11(4):32-37. |
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| Authors: | Cat Yidong Yang Bing Tang Junbiao |
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| Abstract: | Using by the three-demension T. Kohonen self-organizational artificial nerve network, this paper analysed the data of loess porosity in Luochuan area and set up the computer intellingence expert system of loess porosity calculation. The result shows that the nerve network method is quite effective in the classification and differentiation of loess porosity. |
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| Keywords: | quantitaive study Luochuan loess artificial nerve network three-demension T Kohonen self-organizaton model |
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