自组织人工神经网络在隐伏矿定位预测中的应用  

Self-Organized Artificial Neural Networks in Underlying Ore Localization Forecast

作　　者：宁德琼[1] 朱春鸯[1] 

机构地区：[1]曲靖师范学院计科系,云南曲靖655000

出　　处：《保山师专学报》2007年第5期83-85,共3页Journal of Baoshan Teachers' College

摘　　要：运用T Kohonen自组织特征映射人工神经网络,对会泽麒麟铅锌矿进行计算机识别,识别成功率达73%。结果表明该方法性能良好,可望能成为隐伏矿定位预测的一种有效的辅助手段。Using T Kohonen from the organization characteristic mapping artificial neural networks, carrying on the computer recognition in Huize Unicorn lead-zinc mine, the recognition success ratio reaches 73%. The result indicated this method performance is good, hoping to be able to become the underlying ore localization forecast one effective auxiliary method.

关 键 词：隐伏矿定位预测 人工神经网络 T Kohonen自组织 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]