Air quality detection method and air quality detection system

Abstract

The invention relates to an air quality detection method and an air quality detection system. The air quality detection method comprises the steps of obtaining proportions of different chemical radicals during each time period in air by utilizing multi-channel sensors to serve as variables; preprocessing data to obtain an input of a regression device; dividing the whole regression device into a training link and a detection link; in the training link, performing multi-time iteration on each training sample and a corresponding tag to obtain a regression coefficient and auxiliary parameters of a corresponding frequency; and in a test link, realizing estimation of air quality after multi-time superposition by directly utilizing related parameters and the regression coefficient obtained by training. According to the method and the system, the mapping from an input feature to a predicted value can be quickly and accurately finished for multivariant nonlinear regression problems at the same time, so that more accurate detection in environment monitoring can be realized conveniently.

Description

technical field [0001] The invention belongs to the field of environmental monitoring, and in particular relates to an air quality detection method and a detection system, in particular to an air quality detection method and a detection system based on cascade regression Chebyshev polynomial fitting. Background technique [0002] In the face of society's increasing concerns about air quality, how to accurately detect the harmful components in the air has become a topic worthy of research by researchers. For the practical mathematical problem of environmental monitoring, the multivariate nonlinear method is an ideal one among many core technologies. [0003] Among the different multivariate nonlinear methods, the second kind of Chebyshev polynomial regression method, which has better advantages and theoretical basis, is a relatively new nonlinear regression method. [0004] However, this method has the same defect as other polynomial regression methods, that is, the number o...

AI Technical Summary

Problems solved by technology

The reason can be attributed to the fact that the core method of this type of method still uses linear regression. Even if the form of cascade is adopted, if the system is too complicated, we cannot obtain satisfactory results through this type of regression method.

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