摘要
将自适应共振理论网络应用于煤炭资源资产分类,以基于聚类的综合评判模糊数学模型的分类结果作为选择训练样本的基础,建立了自适应神经网络分类模型.网络不仅能得到理想的输出结果,而且能准确地进行煤炭资源资产分类.分类结果表明,用自适应共振理论网络进行分类具有分类稳定、结果可靠等特点.
The ARTⅡ networks are applied to classify assets of coal resources in this paper. The classification results by the fuzzy synthetic judgment models based on cluster being as the base for choosing the patterns, self-organizing networks model to classify is given. Ideal output results have been achieved in training the networks to learn the patterns and in classifying the coal resources assets.The results show that the ARTⅡ network has some advantages such as stability and reliability.
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2002年第6期566-569,共4页
Journal of China Coal Society
基金
山东省自然科学基金资助项目(Q99G14)
关键词
自适应共振理论
煤炭资源
分类
矿井
模糊数学
coal resources assets
adaptive resonance theory(ARTⅡ)
classification
