Finding exact number of peaks in broadband UV-vis spectra using curve fitting method based on evolutionary computing

Abstract

High performance calculations are needed in order to resolve analytic signals of the day. However, it requires very long periods of time to perform these calculations with single processor systems. In order to reduce these calculation times, there is a need to turn to parallel programming algorithms that share more than one processor. Recently, solving complex problems with genetic algorithms has been widely used in computational sciences. In this work, we show a new method of curve fitting via genetic algorithm based on Gaussian functions, for deconvolution of the overlapping peaks and find the exact number of peaks in UV-VIS absorption spectroscopy. UV-VIS spectra are different than other instrumental analysis data. The resolution of UV-VIS spectra are complicated since the absorption bands are strongly overlapped. Useful information about molecular structure and environment can often be obtained by resolving these peaks properly. The algorithm was parallelized with the island model in which each processor computes a different population. This method has been used for resolving of the UV-VIS overlapping spectrum. The method particular algorithm is robust against bad resolution or noise. The results clearly show the effectiveness of the proposed method.