In order to overcome the difficulty in on-line measurement of five-day biochemical oxygen demand ( BOD5) during the wastewater treatment,by taking into consideration the nonlinearity and multivariant coupling characteristics of wastewater treatment process,a robust nearest correlation algorithm based on Jolliffe parameters and correlation data selection algorithm is proposed,which is then combined with the recursive partial least square
algorithm and the linear bias compensation algorithm to improve the conventional JIT ( Just-in-Time) algorithm. Finally,the enhanced JIT algorithm is used to build an on-line soft-sensing model of BOD5. The results of simulation show that the enhanced JIT algorithm outperforms the conventional JIT and RPLS algorithms in terms of on-line prediction accuracy,adaptability and robustness of soft sensing.