US 2024/0403637 A1 · STORAGE MEDIUM STORED WITH MACHINE LEARNING PROGRAM, METHOD, AND DEVICE

Abstract

A machine learning device includes a processor that executes a procedure. The procedure includes: based on route information indicating movement conditions of a plurality of respective moving bodies in a specific geographical range at each of a plurality of time points, generating traffic flow information indicating a number of moving bodies located at respective route segments within the specific geographical range for each of the plurality of time points; and by using training data that includes the traffic flow information as input feature values and includes information indicating a degree of congestion of traffic in the specific geographical range at a time point corresponding to the traffic flow information as label information, training a machine learning model for deriving a degree of congestion of traffic corresponding to traffic flow information.

Claims15

Dependent claims

A non-transitory recording medium storing a program that is executable by a computer to perform a machine learning process comprising:

based on route information indicating movement conditions of a plurality of respective moving bodies in a specific geographical range at each of a plurality of time points, generating traffic flow information indicating a number of moving bodies located at respective route segments within the specific geographical range for each of the plurality of time points;
and
by using training data that includes the traffic flow information as input feature values and includes information indicating a degree of congestion of traffic in the specific geographical range at a time point corresponding to the traffic flow information as label information, training a machine learning model for deriving a degree of congestion of traffic corresponding to traffic flow information.

A machine learning method comprising:

based on route information indicating movement conditions of a plurality of respective moving bodies in a specific geographical range at each of a plurality of time points, generating traffic flow information indicating a number of moving bodies located at respective route segments within the specific geographical range for each of the plurality of time points;
and
by a processor, using training data that includes the traffic flow information as input feature values and includes information indicating a degree of congestion of traffic in the specific geographical range at a time point corresponding to the traffic flow information as label information, training a machine learning model for deriving a degree of congestion of traffic corresponding to traffic flow information.

A machine learning device comprising:

a memory, and
a processor coupled to the memory, the processor being configured to execute processing, the processing including:
based on route information indicating movement conditions of a plurality of respective moving bodies in a specific geographical range at each of a plurality of time points, generating traffic flow information indicating a number of moving bodies located at respective route segments within the specific geographical range for each of the plurality of time points;
and
by using training data that includes the traffic flow information as input feature values and includes information indicating a degree of congestion of traffic in the specific geographical range at a time point corresponding to the traffic flow information as label information, training a machine learning model for deriving a degree of congestion of traffic corresponding to traffic flow information.

2 more elements

Dependencies are inferred from the claim text.

Storage medium stored with machine learning program, method, and device

Life of this patent

Storage medium stored with machine learning program, method, and device

Life of this patent

Abstract

Claims15