Flow field prediction device, learning device, flow field prediction program, and learning program

A flow field prediction device comprising:

• a memory;
• and
• a processor, wherein the processor is configured to:
• provide a machine learning model, by:
• receiving a plurality of instances of input data, each instance of input data relating to buildings in a city block including a plurality of buildings;
• analyzing each instance of input data according to a low-accuracy computation method, obtaining a low-accuracy analysis result, and setting the low-accuracy analysis result as a first element in paired training data;
• analyzing each instance of input data according to a high-accuracy computation method, obtaining a high-accuracy analysis result, and setting the high-accuracy analysis result as a second element in the paired training data;
• and
• training the machine learning model using the paired training data, wherein each low-accuracy analysis result is used as initial data and the high-accuracy analysis result is used as correct answer data;
• receive a new input of a new city block including a new plurality of buildings that is set as a target region;
• perform the low-accuracy computation method on the new input in order to provide a new low-accuracy analysis result;
• and
• use the machine learning model to apply an adjustment to the new low-accuracy analysis result in order to provide a final prediction, wherein providing the final prediction is performed without performing the high-accuracy computation method on the new input.