Adaptive Fuzzy Predictive Approach in Control

Anton A. Romanov (), Aleksey A. Filippov and Nadezhda G. Yarushkina
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Anton A. Romanov: Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia
Aleksey A. Filippov: Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia
Nadezhda G. Yarushkina: Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia

Mathematics, 2023, vol. 11, issue 4, 1-18

Abstract: This article studies the approach to solving the problem of controlling the complex organizational and technical systems based on hybrid models. We propose a new component of intelligent decision support that is integrated with control systems. The proposed component is based on fuzzy logic and knowledge engineering. We present a model of ontology to form the context of data analysis and time series modeling. The ontological context allows us to represent trends of the analyzed object indicators. An expert can add a set of fuzzy rules to the ontology for systems control based on the fuzzy inference. The proposed approach allows reducing the time of analysis and interpretation of the results. Experimental results confirm the correctness and effectiveness of the approach proposed in this article.

Keywords: time series; context; tendencies; predictive analytic; ontology (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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