摘要
利用高碳当量灰铸铁组织强度试验数据,提出了一种基于支持向量机理论的灰铸铁强度预测模型。与多元线性回归、模糊回归和自适应模糊神经网络相比,该模型学习精度高且具有较好的泛化能力,能取得较好的预测效果。
On the basis of the experimental data of microstructure and strength for gray cast iron with high carbon equivalent, a model of support vector machine for gray cast iron prediction was established. Comparing with the models based on multiple statistic analysis, generalized regress-ion neural network or adapted fuzzy neural network model, it shows better learning precision and generalization.
出处
《铸造》
CAS
CSCD
北大核心
2006年第7期711-714,共4页
Foundry
关键词
灰铸铁
支持向量机
支持向量回归机
gray cast iron
support vector machine
support vector regression machine
