1) metering of molten iron
铁水计量
2) Railway Measurement
铁路计量
3) hot metal output
铁水产量
4) quality of molten iron
铁水质量
1.
By a lot of exprerimental studies and theoretic analysis, the influence factors of silicon content in molten iron were found, the good methods smelting were abtained in low silicon, so that molten iron could be smelt in low Si and the quality of molten iron will be improved distinctly.
通过对太钢高炉降硅冶炼进行大量的理论分析与实验研究,得出了铁水硅质量分数的影响因素,找到了降硅冶炼的有效途径,达到铁水低硅冶炼的目的,铁水质量有了明显的提高。
2.
The quality of molten iron is a main contradiction influencing the quality of castings,in which the purity of molten iron is the weakest link to the quality of molten iron.
铁水的质量是影响铸件产品质量的主要矛盾,其中铁水纯净度是影响铁水质量的薄弱环节。
3.
The quality of molten iron is a main condition influencing the quality of castings The pureness of molten iron is a weakest link to the quality of molten iron.
铁水的质量是影响铸件产品质量的主要因素,其中铁水纯净度是影响铁水质量的薄弱环节。
5) silicon content in molten iron
铁水含硅量
1.
With fuzzy theory and stochastic theory,a new intelligent model is developed to approach the random nonlinear dynamic system of the change of silicon content in molten iron,where noise influencing the fuzzy prediction system is thoroughly considered.
该文在考虑了具有模糊化和非模糊化的模糊逻辑系统用于高炉铁水含硅量[Si]时各种噪声干扰的同时,把模糊数学理论和随机系统理论结合在一起,建立了一种新的高炉铁水含硅量[Si]的智能预报模型,该模型是由非单值模糊化、模糊规则库、模糊推理机、特殊非模糊化构成的随机模糊神经网络逻辑系统。
2.
In this paper,ANN(Artificial Neural Network)method is applied to predict the silicon content in molten iron,Several variables have been selected,and a three layers BP(Background Propagation)neural network model is set up.
讨论了人工神经元网络（ＡＮＮ）方法在铁水含硅量预报上的应用策略。
6) silicon content in hot metal
铁水含硅量
1.
Prediction of silicon content in hot metal based on EMD-SVM nonlinear combined model;
EMD-SVM非线性组合模型对高炉铁水含硅量的预测
2.
It is essential to predict silicon content in hot metal accurately for the purpose of controlling blast furnace under good operation condition.
准确预测铁水含硅量是有效控制高炉的前提，人工智能专家系统已在铁水硅含量预测方面取得显著进展，但专家系统在知识获取方面存在不足。
3.
It decomposes the time series of original silicon content in hot metal to different layers through wavelet analysis.
先用小波变换将铁水含硅量的时间序列分解成不同的高频和低频层次,对不同层次构建支持向量机模型进行预测,然后通过序列重构得到原始时间序列的预测结果。
补充资料：长度计量(见几何量计量)
长度计量(见几何量计量)
length measurement: see geometrical quantity metrology
由。飞州ulil心闪长度计l(le理户~~m)童。见几何童计
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条