Methods for predicting economic state and establishing economic state prediction model and corresponding apparatuses

A method for establishing an economic state prediction model, wherein the method comprises:

• acquiring, from map application data, geographic location point active data in M consecutive time frames respectively for a to-be-predicted region;
• and acquiring, from an economic indicator database, actual economic indicator data of the to-be-predicted region in the M time frames respectively, the M being a positive integer greater than 1;
• and
• training a time series model by taking the acquired geographic location point active data and actual economic indicator data in the M consecutive time frames as training data, to obtain an economic state prediction model for the to-be-predicted region;
• the economic state prediction model being configured to output, according to geographic location point active data of the to-be-predicted region in N historical time frames before a to-be-predicted future time frame, economic indicator data of to-be-predicted region in the to-be-predicted time frame, the N being a positive integer, M≥N.

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively connected with 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 enable the at least one processor to perform a method for predicting an economic state, wherein the method comprises:
• acquiring, from map application data, geographic location point active data in N historical time frames before a to-be-predicted future time frame respectively for a to-be-predicted region, the N being a positive integer;
• and
• inputting feature vectors of the geographic location point active data in the N historical time frames before the to-be-predicted time frame into a pre-trained economic state prediction model, to obtain economic indicator data of the to-be-predicted region in the to-be-predicted time frame.

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively connected with 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 enable the at least one processor to perform a method for establishing an economic state prediction model, wherein the method comprises:
• acquiring, from map application data, geographic location point active data in M consecutive time frames respectively for a to-be-predicted region;
• and acquire, from an economic indicator database, actual economic indicator data of the to-be-predicted region in the M time frames respectively, the M being a positive integer greater than 1;
• and
• training a time series model by taking the acquired geographic location point active data and actual economic indicator data in the M consecutive time frames as training data, to obtain an economic state prediction model for the to-be-predicted region;
• the economic state prediction model being configured to output, according to geographic location point active data of the to-be-predicted region in N historical time frames before a to-be-predicted future time frame, economic indicator data of to-be-predicted region in the to-be-predicted time frame, the N being a positive integer, M≥N.

A non-transitory computer-readable storage medium storing computer instructions therein, wherein the computer instructions are used to cause the computer to perform a method for establishing an economic state prediction model, wherein the method comprises:

• acquiring, from map application data, geographic location point active data in M consecutive time frames respectively for a to-be-predicted region;
• and acquiring, from an economic indicator database, actual economic indicator data of the to-be-predicted region in the M time frames respectively, the M being a positive integer greater than 1;
• and
• training a time series model by taking the acquired geographic location point active data and actual economic indicator data in the M consecutive time frames as training data, to obtain an economic state prediction model for the to-be-predicted region;
• the economic state prediction model being configured to output, according to geographic location point active data of the to-be-predicted region in N historical time frames before a to-be-predicted future time frame, economic indicator data of to-be-predicted region in the to-be-predicted time frame, the N being a positive integer, M≥N.