Düşük Sükroz Derişimlerinin Görünür Bölge Spektroskopisi ve Yapay Sinir Aǧları ile Kestirimi

Abstract

Low sucrose concentrations in solutions is estimated by means of localized surface plasmon resonance of immobilized gold nanoparticles. The ultraviolet-visible spectra (UV-Vis) of samples with different sucrose concentrations were prepared and used to train artificial neural networks. In our study, MATLAB Neural Networks Toolbox was used and effect of different input sizes and network structures on the estimation accuracy is investigated. It is observed that using complete spectrum instead of peak point results in higher accuracy.