摘要
用层状神经网络学习识别法对湘南铅、锡矿的化探、物探数据进行了分类研究。结果表明,对铅、锡矿已知样本集的再认正确率均达100%。对待查样本的识别也取得了好效果。
A parallel massively neural network was used to classify the geochemical-geophysical data froma Pb-Sn Mine in southern Hunan.Results obtained show that for known samples either of Pb and Snores,the rate of accurate judgement in either case is up to 100%,while for unknown samples it isbetter than that obtained by conventional statistical pattern recognition technique.The parallel massi-vely neural network is effective in learned classification of geophysical-geochemical data and its effe-ctiveness depends only upon the choice of training sets.
出处
《地质与勘探》
CAS
CSCD
北大核心
1992年第2期47-50,共4页
Geology and Exploration
