A self-learning algorithm for detection of biological aerosols in the air
Автор: Ermakov S.М., Rukavishnikova Anna Igorevna, Volchek A.O., Kochelaev E.A.
Журнал: Научное приборостроение @nauchnoe-priborostroenie
Рубрика: Системный анализ приборов и измерительных методик
Статья в выпуске: 2 т.25, 2015 года.
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We propose an algorithm that uses data from the particle fluorescence spectrometer in order to take decision on presence of known pathogens in the air. Density estimates of measurements for particles of the known substances are constructed, percentage concentration of aerosol particles in the air is estimated. Decision on detection of dangerous substances is made with the use of thresholds, calculated at the training stage. The results of testing the algorithm are discussed.
Device, em-algorithms, mixture of distributions, function of maximum likelihood, density estimate, experimental data, particle fluorescence spectrometer
Короткий адрес: https://sciup.org/14264972
IDR: 14264972
