A soft sensing model for norm vacuum of condensor based on data fusion is proposed due to the enhancement of the accuracy and reliability.
为了提高凝汽器真空应达值预测的准确性和可靠性，提出了基于数据融合的凝汽器真空应达值软测量方法。
Through measuring the electric current signal, the soft sensing model used for tool wear estimation based on stochastic fuzzy neural network(SFNN) is presented in this paper.
本文通过检测电流信号基于随机模糊神经网络建立了刀具磨损量的软测量模型。
The proposed method has been applied to the fermentation process to develop a soft sensing model so as to estimate the products concentration on-line in penicillin fermentation.
同时，将这一方法应用于生物发酵过程，建立了青霉素发酵过程中产物浓度的软测量模型，实现了青霉素浓度的在线预估。
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