Chemical Identification from Raman Peak Classification Using Fuzzy Logic and Monte Carlo Simulation

In spite of the wide use Raman spectroscopy for chemical analysis in different fields, not any automated identification spectra is universally adopted. However, interest this field witnessed by large number papers published last decades. The problem Raman-spectra classification becomes particularly challenging when low irradiation requested, either safety reasons or to avoid target photodegradation. This often leads characterized a signal-to-noise ratio, where methods based on correlation usually fail. For reason, method peak through FMFs presented, discussed and validated over set samples. particular, Monte Carlo simulation has been employed determine best parameters fuzzy membership functions performances procedure. ROC curves have analyzed, AUC accuracy are as key evaluate amounts ammonium nitrate (from 300 1500 μg) laser exposure levels 3.1 250 mJ/cm2).