CONTROL SYSTEM WITH MACHINE LEARNING TIME-SERIES MODELING

摘要

#$%^&*AU2018217286B220190801.pdf#####ABSTRACT A control system to control devices based on an unsupervised machine learning modeling, the control system including an artificial intelligence server including at least one processor, a data storage system to store historic time-series data for independent variables and a dependent variable, and a time series forecasting model, and an unsupervised machine learning modeling system including machine readable instructions stored on a nontransitory computer readable medium and executed by the artificial intelligence server to build the time series forecasting model from the stored historic time-series data according to an unsupervised machine learning function, wherein the time series forecasting model includes the independent variables from the stored historic time-series data and the dependent variable from the stored historic time-series data, and wherein the building of the time series forecasting model includes determining a time-varying parameter (P) for each of the independent variables and for continuous consecutive time intervals of the stored historic time-series data, restricting a variance of at least one of the P's if overfitting for the time series forecasting model is estimated to occur, and for each of the independent variables, multiplying the independent variable with the time-varying parameter for the independent variable, and apply the time series forecasting model to a data set, wherein the applying of the time series forecasting model includes estimating a contribution of each of the independent variables for each of the consecutive time periods to the dependent variable, and generating predictions or instructions as input to control operations performed by at least one device according to the estimated contributions of the independent variables.1/13 (n C 00 C40 00 '-Sf