Computer-aided measuring system based on an artificial neural network for estimating atmospheric parameter

Авторы: Chulichkov A., Nikitin S., Borovski A., Postylyakov O.
Сборник: PROCEEDINGS OF ITNT 2021 - 7TH IEEE INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND NANOTECHNOLOGY
Год издания: 2021
Место издания: IEEE
Первая страница: 1
Последняя страница: 5
Номер статьи: 275
DOI: 10.1109/ITNT52450.2021.9649031
Аннотация: Methods of the linear theory of computer-aided measuring systems are well developed. They allow obtaining the most accurate estimates of the parameters of the object under study from the measurement data (the reduction of measurement), as well as monitoring the consistency of the used mathematical model with the measurement result. In this paper, these methods are generalized to a class of nonlinear estimates implemented using neural networks. Sample estimates of the accuracy of the reduction of measurements and the agreement of the model with the data are used. The approach is applied for estimating atmospheric parameters based on spectral measurements of scattered solar radiation.
Добавил в систему: Чуличков Алексей Иванович

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