Fig. 1. Flowchart of IERT algorithm

Fig. 2. Flowchart of KPCA algorithm

Fig. 3. Schematic diagram of experimental device

Fig. 4. Flowchart of extremely randomize trees algorithm

Fig. 5. Model diagram and physical diagram of the spectrometer

Fig. 6. Transmission spectra of multi-component mixed solutions

Fig. 7. Test set experimental results of IERT algorithm for COD, BOD₅, TOC multi-component mixed solutions
(a): Comparison of the true value and the prediction value of COD;(b): Comparison of the true value and the prediction value of BOD₅;(c): Comparison of the true value and the prediction value of TOC;(d): Relative error of COD prediction value; (e): Relative error of BOD₅ prediction value;(f): Relative error of TOC prediction value

Table 1. The sample characteristics table of multi-component mixed solution dataset of COD, BOD₅ and TOC

Table 2. The sample characteristics table of multi-component mixed solution dataset of NO₃-N, turbidity and colority

Table 3. Experimental results of IERT algorithm using different kernel functions

Table 4. The experimental results of the sigmoid kernel function when the number of principal components is selected as n

Table 5. Experimental results of sigmoid kernel function under different parameters c

Table 6. Experimental results of IERT algorithm under different parameters m

Table 7. Comparison of evaluation parameters between IERT algorithm and 4 prediction algorithms for COD, BOD₅, TOC multi-component mixed solutions

Table 8. Comparison of evaluation parameters between IERT algorithm and 4 prediction algorithms for NO₃-N, turbidity, colority multi-component mixed solutions

Table 9. Comparison of calculation time between IERT algorithm and 4 prediction algorithms