以热轧工艺中冶金物理学理论为依据，建立了组织性能预报模型。
The establishment of microstructure and properties forecast model is based on metallurgical physics theory on hot rolling process.
采用神经网络方法建立了重轨生产性能预报模型，并通过模型结构优化提高了模型预报的可靠性。
A mathematic model to predict the mechanical properties of heavy rail steel has been developed by means of neural network according to the demand of production.
有关尼古丁的模型复杂程度较低，过滤嘴的通风性能再次成为最大的预报器，影响比例占到40%，与此同时，烟草重量和过滤嘴长度同样产生重要影响。
Nicotine yielded a less complex model, with ventilation again serving as the largest predictor (40% of variance), with tobacco weight and filter length serving as significant contributors.
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