A fuzzy data-driven paradigmatic predictor

Amirjavid, Farzad; Nemati, Hamidreza; Barak, Sasan

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.

Citation

Amirjavid, F., Nemati, H., & Barak, S. (2019). A fuzzy data-driven paradigmatic predictor. IFAC-PapersOnLine, 52(13), 2366-2371. https://doi.org/10.1016/j.ifacol.2019.11.560

• Journal Article Type: Conference Paper
• Conference Name: 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019
• Conference Location: Berlin, Germany, 28–30 August 2019
• Acceptance Date: Dec 31, 2019
• Publication Date: Sep 1, 2019
• Deposit Date: Apr 21, 2020
• Journal: IFAC-PapersOnLine
• Print ISSN: 1474-6670
• Electronic ISSN: 2405-8963
• Publisher: International Federation of Automatic Control (IFAC)
• Peer Reviewed: Peer Reviewed
• Volume: 52
• Issue: 13
• Pages: 2366-2371
• DOI: https://doi.org/10.1016/j.ifacol.2019.11.560
• Keywords: Control and Systems Engineering
• Public URL: https://uwe-repository.worktribe.com/output/5876337