Prediction of elemental concentration using of laser induced breakdown spectroscopy aided by artificial neural network, statistical methods of autoregressive integrated moving average model and support vector regression and their combination

In this paper, by using of laser induced breakdown spectroscopy (LIBS) method, the elemental concentrations existed in standard aluminum alloys are measured quantitatively. Pulse Nd:YAG at 1064 nm is irradiated on Al samples and analysis performed created plasma. Among different methods for estimation concentration elements samples, artificial neural network (ANN), Support vector regression, autoregressive integrated moving average model (ARIMA), kernelized support regression (KSVR) combined method KSVR-ARIMA utilized prediction element Fe, Cu, Zn, Mg, Mn, Si obtained results from these compared together. The extracted show that reports best values least error most elements.