Patent ID: 11959900
Assignee: CENTRAL SOUTH UNIVERSITY
Field: Measurement (Instruments)
Classification: CPC G  B | IPC B  G

Claim 5:
6. The method according to claim 5, wherein the step of establishing the spatial mixture model for multi-pollutant concentration indexes in the step S4 is, specifically, to establish the spatial mixture model for multi-pollutant concentration indexes in the following steps:
1) acquire air quality data information of the associated air quality monitoring stations and the pollutant data information on the train side;
2) divide data acquired in the step 1) into a training set and a verification set;
3) train a predictor model by taking the air quality data information of the associated air quality monitoring stations as an input of the predictor model, and by taking the pollutant data information on the train side after a Δt moment as an output of the predictor model, thereby obtaining a pollutant concentration prediction model for the associated air quality monitoring stations in a step of Δt;
4) perform, according to the pollutant concentration prediction model for the associated air quality monitoring stations obtained in the step 3), a plurality of steps of prediction on air quality of positions where the associated air quality monitoring stations are located, thereby obtaining an air quality prediction set of the associated air quality monitoring stations; and
5) train and establish a deep belief network model by taking a multiplication combination term of the air quality data information of the associated air quality monitoring stations and a degradation degree imposed by the associated air quality monitoring stations on the air quality on the train side after the T minutes as an input of the deep belief network model and by taking the pollutant data information on the train side as an output of the deep belief network model, thereby obtaining the spatial mixture model for multi-pollutant concentration indexes.