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A Fuzzy Data-Driven Paradigmatic Predictor

Research output: Contribution to journalJournal article

Forthcoming
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<mark>Journal publication date</mark>20/02/2019
<mark>Journal</mark>IFAC-PapersOnLine
Number of pages6
Publication statusAccepted/In press
Original languageEnglish

Abstract

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.