Decomposition of Spectral Band into Gaussian Contours Using an Improved Modification of the Gender Genetic AlgorithmстатьяИсследовательская статья
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Дата последнего поиска статьи во внешних источниках: 15 февраля 2024 г.
Аннотация:One of the methods for analysis of complex spectral bands (especially for spectra of liquid objects) is their decomposition into a limited number of spectral curves with physically reasonable shapes (Gaussian, Lorentzian, Voigt etc.). Consequent analysis of the dependencies of the parameters of these contours on some external conditions in which the spectra are obtained may reveal some regularities bearing information about the physical processes taking place in the object. The problem with the required decomposition is that such decomposition in presence of noise in spectra is an incorrect inverse problem. Therefore, this problem is often solved by advanced optimization methods less subject to be stuck in local minima, such as genetic algorithms (GA). In the conventional version of GA, all individuals are similar regarding the probabilities and implementation of the main genetic operators (crossover and mutation) and the procedure of selection. In their preceding studies, the authors tested gender GA (GGA), where the individuals of the two genders differ by the probability of mutation (higher for males) and by the procedures of selection for crossover (with the number of crossovers limited for females). In this study, we introduce additional differences between the genders in the procedures of selection and mutation. The improved modification of GGA is tested by comparison of the efficiency conventional GA, GGA and three versions of GGA with and without subsequent gradient descent in solving the problems of decomposition of the Raman valence band of liquid water into Gaussian contours.