A soft sensing modeling method based on continuous hidden Markov model(CHMM) is developed to deal with
the problem that some biologic variables cannot be measured directly online in fermentation process. In order to reduce
the computation quantity of modeling process, improved minimum classification error criteria is used to train the CHMMbased
soft sensor. Meanwhile, a soft sensing credibility evaluation index is proposed to avoid blindness problem during the
practical application of soft sensing result to monitoring in fermentation process. The testing result shows the effectiveness
of the proposed method and the practical significance of the credibility evaluation index.