Training method for air quality prediction model, prediction method and apparatus, device, program, and medium

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively connected to the at least one processor;
• wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to cause the at least one processor to execute a training method for an air quality prediction model, wherein the training method comprises:
• dividing a target monitoring range into a plurality of regions, wherein the plurality of regions comprise measurement regions with air quality measurement values and prediction regions without the air quality measurement values, and acquiring the air quality measurement values in the measurement regions;
• pre-training the air quality prediction model by adopting a pre-training sample and a pre-training objective function, wherein the pre-training sample comprises the measurement values;
• and
• training the pre-trained air quality prediction model by adopting a formal training sample and a formal training objective function, wherein the formal training sample comprises the measurement values;
• wherein the air quality prediction model is configured to predict air quality of the plurality of regions according to spatial information, historical information and environmental information.

A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute a training method for an air quality prediction model, wherein the training method comprises:

• dividing a target monitoring range into a plurality of regions, wherein the plurality of regions comprise measurement regions with air quality measurement values and prediction regions without the air quality measurement values, and acquiring the air quality measurement values in the measurement regions;
• pre-training the air quality prediction model by adopting a pre-training sample and a pre-training objective function, wherein the pre-training sample comprises the measurement values;
• and
• training the pre-trained air quality prediction model by adopting a formal training sample and a formal training objective function, wherein the formal training sample comprises the measurement values;
• wherein the air quality prediction model is configured to predict air quality of the plurality of regions according to spatial information, historical information and environmental information.