Size concentration modeling method for slashing process based on output variable dynamic correction

A size concentration modeling method based on output variables dynamic correction is proposed for the sample data with asynchrony characteristics. In which, the modified recursive least square algorithm is used for continuous sample data. And by decay factor, the effect of new data is strengthened and the effect of old data is retained. For intermittent sample data, principal component regression is improved precision of size concentration model. Finally, the output of size concentration model is corrected by the output variables dynamic correction method.