1.
Application of WA-SVM Combined Model to Predict Silicon Content in Hot Metal
基于WA-SVM模型的高炉铁水含硅量预测
2.
On-ine Realization of Predicting Hot Metal Silicon by Computer
高炉铁水含硅量预测的计算机在线实现
3.
Application of Leading indictor predicting hot metal silicon;
提示序列在高炉铁水含硅量预测中的应用
4.
Engineering Calculation for BF Temperature and Si Content in Hot Metal and Its Application
高炉炉温与铁水含硅量工程推算法及应用
5.
Influence of Operating Parameters on Hot Metal Silicon Content of Xing steel BF
操作制度对邢钢2#高炉铁水含硅量的影响
6.
Application of time series method predicting hot metal silicon for No.6 BF in Limfen steel works;
时间序列方法在临钢六号高炉铁水含硅量预测中的应用
7.
Multi-fractal identification of the fluctuation of silicon content in blast furnace hot metal based on multi-resolution analysis
基于多分辨分析的高炉铁水含硅量波动多重分形辨识
8.
The Predicted System of Si Content in Molten Iron Based on GA-BP Network;
基于GA-BP网络的铁水硅含量预测系统
9.
The support vector regression based on the chaos particle swarm optimization algorithm for the prediction of silicon content in hot metal
铁水硅含量的混沌粒子群支持向量机预报方法
10.
First-hand Experience and Second-hand Knowledge in Prediction of Silicon Content in Hot Metal Tapped from Blast Furnace;
高炉铁水硅含量预测中的直接经验和间接经验
11.
SFNN Model for Prediction of Silicon Content in Molten Iron;
随机模糊神经网络模型预测铁水硅含量
12.
Influence of Metal Temperature,Slag Basicity and Initial Si Content on Demanganization of Carbon-Saturated Hot Metal
铁水温度、炉渣碱度和初始硅含量对碳饱和铁水脱锰的影响
13.
A Neural Network Model Predicting the Silicon Content in Hot Metal at No.3 Blast Furnace of No.2 Ironworks TangShan Iron and Steel Co.;
唐钢二炼铁厂3号高炉铁水硅含量神经网络预报模型
14.
The Realization of the Iron-smeltery Integrated Automation System and the Model to Predict Silicon Content in Hot Metal Under CIPS;
CIPS结构下炼铁厂集成自动化系统及高炉铁水硅含量预报实现
15.
ICP-AES Determination of Ferrosilicon Si-Mn Content of Lead and Zinc
ICP-AES法测定硅铁、硅锰中铅和锌含量
16.
" Methods for chemical analysis of iron,steel and alloy--The perchloric acid dehydration gravimetric method for the determination of silicon content"
GB/T223.60-1997钢铁及合金化学分析方法高氯酸脱水重量法测定硅含量
17.
Fuzzy rules Based on Support Vector Machines and its Application to the Prediction of Silicon Content in Hot Metal
基于支持向量机的模糊规则获取及其在铁水硅含量预报中的应用
18.
Prediction of Silicon Content in Hot Metal Based on SVR Optimized by Chaos Particle Swarm Optimization
基于混沌粒子群支持向量回归的高炉铁水硅含量预测