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中文摘要：
传统划分菌体生长时期是建立在菌体浓度的基础上，并未考虑菌体生长过程中的影响因素。本文在分析菌体生长过程的基础上，建立了ART2神经网络来实时判断菌体所处的生长阶段。模型的特征向量采用菌体浓度以及反映菌体生长状况的呼吸参数和其所处的环境因素参数。实验表明，该方法能准确地判断菌体所处的生长阶段。
英文摘要：
Different phases of fermentation are conventionally classified by biomass concentration. Even with an accurate evaluation of the cell concentration, it is difficult to estimate the growth phase of a particular microorganism. A new ART2 method was developed to identify different phases in the growth cycle of fermentation. Biomass concentration, respiration parameters representing live behavior and environmental variances were introduced to raise the accuracy of identification. The required data were obtained from a series of slide windows in the process. The experiment results show that this method is accurate and effective.
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