Urban air quality grade predicting method based on multi-field characteristics

Abstract

The invention relates to an urban air quality grade predicting method based on multi-field characteristics. The method comprises a data preprocessing stage, a training stage and a predicting stage. In the data preprocessing stage, mesh generation is carried out to obtain a training sample, and a training data set is obtained. In the training stage, the optimal parameter of a conditional random field model is estimated, an optimal model shown in the specification is obtained, and the conditional random field model is output. In the predicting stage, the maximum output sequence, shown in the specification, of the conditional probability P(Y / X<f>) is obtained by combining the viterbi algorithm and the conditional probability model shown in the specification and obtained in learning of the training stage, and a prediction result is output. The AQI grade can be predicted more accurately, the AQI grade prediction in the following time quantum of all stations is carried out, and the requirement for selecting the time quantum with the high air quality to go out and take activities of people is met.

Description

technical field [0001] The invention relates to a method for predicting city AQI grades, in particular to a method for predicting AQI grades of air quality monitoring stations based on multi-field features. Background technique [0002] Air is a substance that the living things on the earth depend on for survival, and it is an essential substance. Ambient air quality is closely related to people's daily life, and it also plays an important role in the comprehensive evaluation of urban environment. However, with the development of human civilization and economy, air pollution is becoming more and more serious. How to improve air quality and reasonably predict and warn air environment quality is becoming more and more important. According to air quality prediction, people can take corresponding measures such as wearing masks, Try to avoid going out, etc., and protect yourself from air pollutants. [0003] Traditional air quality prediction methods generally only consider the...

AI Technical Summary

Problems solved by technology

On the other hand, the traditional air quality forecast usually predicts the air quality of the next whole day. There is a drawback in this kind of coarse-grained air quality forecast. People who are more sensitive to substances can carry out outdoor activities, but in fact, the air quality in certain time periods (such as 8:00-9:00 am, 5:00-6:00 pm) may be moderately polluted or heavily polluted. People who are more sensitive to air pollution are not suitable for outdoor activities during these time periods

Images