Soft sensor modeling based on improved extreme learning machine algorithm
Congli Mei · Computer Engineering and Applications Journal · 2012
To solve the problem that biomass concentration is difficult to measure directly in the fermentation process,a soft sensor modeling method based on Improved Extreme Learning Machine(IELM)is proposed.The least squares method is combined with the ELM algorithm to calculate the optimal learning parameters.And the training error is used as feedback input to improve the stability and prediction of ELM.In order to further improve the stability of the model,the Lanczos Bidiagonalization(LBD)is used to calculate the output weights.The proposed modeling method is used to construct a novel soft sensor model for the erythromycin fermentation process.Compared with ELM、IRLS-ELM and PL-ELM model,IELM model has higher prediction accuracy and stronger generalization capability.