A Fuzzy Data-Driven Paradigmatic Predictor

Data-driven prediction of future events is to provide decision-makers Predictive Information (PI) to decrease human-error. They usually desire possession of a predictor which works independently from the humanized configurations and works efficiently and accurately. The accurate data-driven prediction of the systems' behavior is the primary focus of this paper. We define the future state of a system is a set of uncertain values, which can be modeled by fuzzy numbers. The future machine state is not very dissimilar to the current status, and the next event is a sort of behavior repetition. The PI also justifies the system being in a trend to achieve a goal, and it counts the unplanned contextual reactions of the system. In this paper, we come up with a fuzzy data-driven predictor application to foretell the system behavior. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.