Application of mixtures of kernels in diesel cetane number measurement with NIR spectra measurement

The most usually used least squares support vector machines(LS-SVM) modeling method In near infrared(NIR) spectra measurement are based on a single kernel function. However, the single kernel function can not describe the whole data very well, thus affecting the LS-SVM modeling results. In this paper, we introduced the mixtures of kernels to replace the original single kernel, then the LS-SVM based on the mixtures of kernels was applied to model prediction. It was proved by the experimental results that the algorithm can obviously improve the model prediction performance of diesel cetane number based on the LS-SVM compared with other methods in existence.