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The predictive ability of different chemometrics methods was determined using five two-component aluminum and bismuth mixtures. The statistical results obtained by applying CWT, PLS, WOSC-PLS and LS-SVM to five synthetic samples are listed in Table 2. As can be seen, the statistical parameters were quite acceptable. For the evaluation of the predictive ability of models, the root mean square error of prediction (RMSEP) and relative standard error of prediction (RSEP) can be used:
formula
11
formula
12
where is the predicted concentration in the sample, is the observed value of the concentration in the sample and n is the number of samples in the validation set. RMSEP and RSEP (%) results for different chemometrics methods are summarized in Table 2. Good results were achieved in chemometrics models, with recovery ranges from 99.3–100.0 and 98.4–100.8% for aluminum and bismuth, respectively. As can be seen, the recovery was also quite acceptable.
Table 2

Mean recovery, RMSEP and RSEP(%) for the simultaneous determination of Al and Bi in various synthetic mixtures by CWT, PLS, WOSC-PLS and LS-SVM methods

 Recovery (%)a
RMSEPb
RSEP (%)c
MethodsAlBiAlBiAlBi
bior 2.4 98.9 98.4 0.130 0.134 2.002 3.053 
Bior 3.9 99.3 100.8 0.112 0.110 1.720 2.510 
Coif 3 98.0 100.5 0.166 0.160 2.554 3.648 
PLS 100.0 99.8 0.110 0.104 1.686 2.370 
WOSC-PLS 98.6 101.6 0.046 0.060 0.701 1.366 
LS-SVM 99.3 100.0 0.021 0.011 0.213 0.165 
 Recovery (%)a
RMSEPb
RSEP (%)c
MethodsAlBiAlBiAlBi
bior 2.4 98.9 98.4 0.130 0.134 2.002 3.053 
Bior 3.9 99.3 100.8 0.112 0.110 1.720 2.510 
Coif 3 98.0 100.5 0.166 0.160 2.554 3.648 
PLS 100.0 99.8 0.110 0.104 1.686 2.370 
WOSC-PLS 98.6 101.6 0.046 0.060 0.701 1.366 
LS-SVM 99.3 100.0 0.021 0.011 0.213 0.165 

aAverage of five determinations.

bRoot mean squares error of prediction.

cRelative standard error of prediction.

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