Abstract: Described are method and apparatus for discriminating whether a time series data is a deterministic chaos or a stochastic chaos. In the method and apparatus, a trajectory parallel measuring method is used to discriminate the observed time series data.

Abstract: A monitoring apparatus for monitoring an operating condition of a system includes a predicting section which generates a data vector whose parameter is determined by a timeseries data of the system and which obtains a prediction value of the timeseries data of a predetermined time future by means of the chaotic inference based on a behavior of attractor which is generated in a reconstruction space by an embedding operation of the data vector. A monitoring section compares the detected value and the prediction value of the timeseries data and decides the condition of the observed system according to the compared result. Therefore, it becomes possible to appropriately and quickly judge as to whether the observed system is in an abnormal condition or not.

Abstract: An apparatus for executing a short-term prediction of chaotic timeseries data includes a parameter determining section that changes each of parameter values according to the dynamics of observed chaotic timeseries data, and a predicting section that predicts a near future value of objective by reconstructing an attractor of timeseries data of the objective data in a multi-dimensional state space and by using vector neighboring to the data vector including the objective data. Therefore, it becomes possible to quickly and accurately execute a short-term prediction of chaotic timeseries data and to be responsive to the changes of the dynamics of the timeseries data.