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- W2370336475 abstract "Due to BP neural networks is defective in rapidity of convergence and apt to trap into local extreme value, this paper bring forward a kind of second training method of the neural network by combining BP algorithm with QPSO algorithm for estimation model of penicillin fermentation concentration. Training and testing the model with penicillin fermentation data-set . Based on this model, QPSO algorithm is applied to optimize trajectories of temperature and pH in each fermentation phase. The experiment results indicates that this model features small training error , high learning speed, well generalization ability , high estimation precision. The model is able to realize multi-step pre-estimate. Optimizing control trajectories of temperature and pH makes the fermentation concentration increase." @default.
- W2370336475 created "2016-06-24" @default.
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- W2370336475 date "2007-01-01" @default.
- W2370336475 modified "2023-09-27" @default.
- W2370336475 title "Modeling and Optimization for Fermentation Process Based on QPSO-ANN" @default.
- W2370336475 hasPublicationYear "2007" @default.
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