Chronological change prediction system

A method for predicting a state of random variables with a graphical model by a chronological change prediction system,

• wherein the chronological change prediction system is configured to store the graphical model,
• wherein an input of the graphical model is a first evidence set at a first time,
• wherein an output of the graphical model is information about states of the random variables at a second time when a first period has passed from the first time, and
• wherein the first evidence set includes probability distributions of all or a part of the random variables, and
• the method comprising:
• obtaining, by the chronological change prediction system, the first evidence set;
• determining, by the chronological change prediction system, whether to convert each of the probability distributions based on a feature value calculated from each of the probability distributions and/or a feature value calculated from a random variable associated in the graphical model with each of the probability distributions;
• converting, by the chronological change prediction system, each probability distribution determined to be converted into a first particular state of a first random variable corresponding to each probability distribution determined to be converted;
• creating, by the chronological change prediction system, a second evidence set from the first evidence set by replacing each probability distribution determined to be converted and included in the first evidence set with the first particular state;
• inputting, by the chronological change prediction system, the second evidence set to the graphical model;
• and
• outputting, by the chronological change prediction system, information about states of the random variables of the second time.

A non-transitory computer readable medium storing a program which causes a chronological change prediction system to predict a state of random variables with a graphical model,

• wherein the chronological change prediction system is configured to store the graphical model,
• wherein an input of the graphical model is a first evidence set at a first time,
• wherein an output of the graphical model is information about states of the random variables at a second time when a first period has passed from the first time,
• wherein the first evidence set includes probability distributions of all or a part of the random variables, and
• wherein the program causes the chronological change prediction system to:
• obtain the first evidence set;
• determine whether to convert each of the probability distributions based on a feature value calculated from each of the probability distributions and/or a feature value calculated from a random variable associated in the graphical model with each of the probability distributions;
• convert each probability distribution determined to be converted into a first particular state of a first random variable corresponding to each probability distribution determined to be converted;
• create a second evidence set from the first evidence set by replacing each probability distribution determined to be converted and included in the first evidence set with the first particular state;
• input the second evidence set to the graphical model;
• and
• output information about states of the random variables of the second time.