Neural network recognition and classification of aerosol particle size distributions / by E. Yee and J. Ho. : DR52-5/11-1990E-PDF

"This paper describes the application of a neural computational network model to the pattern recognition and classification of aerodynamic particle size distributions associated with a number of environmental, bacterial, and artificial aerosols. The aerodynamic particle size distributions are measured in real-time with high resolution using a two-spot He-Ne laser velocimeter. The technique employed here for the recognition and classification of aerosols of unknown origin is based on a three-layered neural network that has been trained on a training set consisting of 75 particle size distributions obtained from three distinct types of aerosols [...] The approach offers the opportunity of recognizing, classifying, and characterizing aerosol particles in real-time according to their aerodynamic particle size spectrum and its high recognition accuracy shows considerable promise for applications to rapid real-time air monitoring in the areas of occupational health and air pollution standards"--abstract.

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publications.gc.ca/pub?id=9.927680&sl=1

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