Information processing apparatus, risk forecasting method, and program

An information processing apparatus comprising:

• a cell division unit that divides a target region into a plurality of cells;
• a generation unit that generates a plurality of combinations of a distribution function spatially and temporally representing a risk distribution in the target region, a spatial parameter of the distribution function, and a temporal parameter of the distribution function;
• a selection unit that computes an evaluation value for each of the combinations, by using risk occurrence history data for each of the cells from among risk occurrence history data of the target region, and selecting one combination from among the plurality of combinations, based on the evaluation value for the each combination;
• and
• an output unit that outputs a risk forecasting result of the target region, by using the one combination selected by the selection unit.

A risk forecasting method executed by a computer, the method comprising:

• dividing risk occurrence history data of a target region into training data used for computing a risk value for each of combinations of a distribution function spatially and temporally representing a risk distribution in the target region, a spatial parameter of the distribution function, and a temporal parameter of the distribution function, and evaluation-value computation data used for evaluating a combination of the distribution function, the spatial parameter, and the temporal parameter;
• selecting one combination from among combinations of the distribution function, the spatial parameter, and the temporal parameter, based on an evaluation value for each of the combinations computed based on a risk value for each of the combinations based on the training data and the evaluation-value computation data;
• and
• outputting a risk forecasting result of the target region, by using the selected one combination.

A risk forecasting method executed by a computer, the method comprising:

• dividing a target region into a plurality of cells;
• generating a plurality of combinations of a distribution function spatially and temporally representing a risk distribution in the target region, a spatial parameter of the distribution function, and a temporal parameter of the distribution function;
• computing an evaluation value for each of the combinations, by using risk occurrence history data for each of the cells from among risk occurrence history data of the target region, and selecting one combination from among the plurality of combinations, based on the evaluation value for the each combination;
• and
• outputting a risk forecasting result of the target region, by using the selected one combination.

A non-transitory computer readable medium storing a program for causing a computer to execute a risk forecasting method, the method comprising:

• dividing risk occurrence history data of a target region into training data used for computing a risk value for each of combinations of a distribution function spatially and temporally representing a risk distribution in the target region, a spatial parameter of the distribution function, and a temporal parameter of the distribution function, and evaluation-value computation data used for evaluating a combination of the distribution function, the spatial parameter, and the temporal parameter;
• selecting one combination from among combinations of the distribution function, the spatial parameter, and the temporal parameter, based on an evaluation value for each of the combinations computed based on a risk value for each of the combinations based on the training data and the evaluation-value computation data;
• and
• outputting a risk forecasting result of the target region, by using the selected one combination.

A non-transitory computer readable medium storing a program for causing a computer to execute a risk forecasting method, the method comprising:

• dividing a target region into a plurality of cells;
• generating a plurality of combinations of a distribution function spatially and temporally representing a risk distribution in the target region, a spatial parameter of the distribution function, and a temporal parameter of the distribution function;
• computing an evaluation value for each of the combinations, by using risk occurrence history data for each of the cells from among risk occurrence history data of the target region, and selecting one combination from among the plurality of combinations, based on the evaluation value for the each combination;
• and
• outputting a risk forecasting result of the target region, by using the selected one combination.