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The fuzzy filter based on the method of areas' ratio
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NSTL
Elsevier
The paper describes a new fuzzy filter based on the method of areas' ratio which allows to reduce noise during filtering signals. To expand the functionality of the method of areas' ratio two computational procedures were developed to eliminate errors inherent in classical defuzzification models, namely a narrow range of defuzzification and insensitivity of a defuzzification model. Presented various computational procedures for the fuzzy filter can change the properties of the output variable resulting. As an example, the proposed mathematical model of the Fuzzy Filter based on the Method of Areas' Ratio illustrated its distinctive characteristics are shown. Firstly, the Fuzzy Filter based on the Method of Areas' Ratio model has the property of continuity. Secondly, computational procedures provide an increase in the performance of the fuzzy filter. Using detailed numerically calculated Root Mean Square Error and Mean Absolute Percentage Error evaluated the proposed model of the fuzzy filter with other filters such as Kalman Filter, Fuzzy Kalman Filter, Ensemble Kalman Filter and Fuzzy Extended Kalman Filter, Basic defuzzification distributions, Fuzzy mean, Quality method, Root mean square and New weighted trapezoid median average. One of the main goals of the article was to confirm the hypothesis about the possibility of using a fuzzy filter based on the method of area's ratio for filtering signals. As well as studies of the sensitivity of the proposed fuzzy filter is based on the Root Mean Square Error and Mean Absolute Percentage Error coefficients. These coefficients were established during the experimental studies and showed that the sensitivity of the fuzzy filter based on the method of area's ratio is better than other filters. (C)& nbsp;2022 Elsevier B.V. All rights reserved.
Fuzzy Kalman FilteringMethod of areas' ratioFF-MARNarrow range of defuzzificationSensitivity of the defuzzification modelKALMAN FILTERDEFUZZIFICATIONSYSTEMEXPECTATION
Bobyr, Maxim, V、Milostnaya, Natalia A.、Bulatnikov, Valentin A.
NSTL
Elsevier
