WANG Guangcheng, LI Xiangyi, and LI Thongxue, Application of Artificial Neural Networks to the Classification of Coal Reserve Assets, J. Univ. Sci. Technol. Beijing, 4(1997), No. 4, pp. 1-4.
Cite this article as:
WANG Guangcheng, LI Xiangyi, and LI Thongxue, Application of Artificial Neural Networks to the Classification of Coal Reserve Assets, J. Univ. Sci. Technol. Beijing, 4(1997), No. 4, pp. 1-4.
WANG Guangcheng, LI Xiangyi, and LI Thongxue, Application of Artificial Neural Networks to the Classification of Coal Reserve Assets, J. Univ. Sci. Technol. Beijing, 4(1997), No. 4, pp. 1-4.
Citation:
WANG Guangcheng, LI Xiangyi, and LI Thongxue, Application of Artificial Neural Networks to the Classification of Coal Reserve Assets, J. Univ. Sci. Technol. Beijing, 4(1997), No. 4, pp. 1-4.
Resources Engineering School, USTB, Beijing 100083, China
中文摘要
Using the classification results by the fuzzy clustering models as the basis for choosing the choosing patterns, a feed forward networks model for classification is given. Remarkable success was achieved in training the networks to learn the patterns and in classifying the coal reserve assets. The results show that the neural network approach for classification has some advantages such as stability and reliability.
Using the classification results by the fuzzy clustering models as the basis for choosing the choosing patterns, a feed forward networks model for classification is given. Remarkable success was achieved in training the networks to learn the patterns and in classifying the coal reserve assets. The results show that the neural network approach for classification has some advantages such as stability and reliability.
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