title: ÐÑÐµÐ½ÐºÐ° Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð² ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ñ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ ÑÐ°ÑÑÐµÑÐ½Ð¸Ñ ÑÐ²ÐµÑÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Estimation of the parameters of dispersive systems by machine learning methods in dynamic light scattering experiments
Creators: name: ÐÐ¾Ð»Ð¾Ð»Ð¾Ð±Ð¾Ð², ÐÐ»ÐµÐºÑÐ°Ð½Ð´Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: Ð¡Ð¿ÐµÐºÑÑÐ¾ÑÐºÐ¾Ð¿Ð¸Ñ Ð»Ð°Ð·ÐµÑÐ½Ð°Ñ
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machine learning

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description: This paper contains research of possibilities of using machine learning algorithms for interpretation of dynamic light scattering experiment results. The purpose of this paper is the development, application and study of the effectiveness of methods and algorithms of machine learning, which make it possible to estimate the parameters of dispersive systems in experiments with dynamic light scattering. In the course of the work, a literature review of dynamic light scattering and machine learning methods was carried out. In this work, theoretical knowledge about the form of the autocorrelation function of the scattered signal was used to generate synthetic data close to the available experimental ones. The paper presents possible operations for preliminary data processing, generation features for the most efficient training of models. Based on the data obtained, a review was made of the effectiveness of various machine learning methods, in particular, the selection of the optimal neural network topology for predicting the parameters of particles from the available scattering signals and their autocorrelation functions. Visualization of the results obtained, comparison of theoretical and practical plots for autocorrelation functions of signal scattering has been carried out.