Monitoring and Prediction of Time Series Based on Fuzzy Cognitive Maps with Multi-step Gradient Methods

Fuzzy cognitive map FCM is a useful tool for modeling systems for time series monitoring and prediction in various fields. This paper is devoted to the analysis of the application of FCM with multistep learning algorithms based on gradient method and Markov model of gradient for multivariate time series monitoring and prediction. Real data from a monitor system mounted in a domotic house were used in learning and testing process. The comparative analysis of two-step method of Markov model of gradient, multi-step gradient method and one-step gradient method from the point of view of the obtained prediction error was performed.