Uncertainty Modeling of Improved Fuzzy Functions With Evolutionary ...
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Jul 16, 2008 · Abstract: This paper introduce a type-2 fuzzy function system for uncertainty modeling using evolutionary algorithms (ET2FF).
The proposed method implements a three-phase learning strategy to capture the uncertainties in fuzzy function systems induced by learning parameters, as well as ...
Oct 22, 2024 · This paper introduce a type-2 fuzzy function system for uncertainty modeling using evolutionary algorithms (ET2FF). The type-1 fuzzy ...
This thesis analyses fuzzy-modeling problems and different approaches to cope with it. It focuses on a novel evolutionary FSM approach–the design of “Improved.
This paper introduce a type-2 fuzzy function system for uncertainty modeling using evolutionary algorithms (ET2FF). The type-1 fuzzy inference systems ...
It demands an identification of many parameters. This thesis analyses fuzzy-modeling problems and different approaches to cope with it. It focuses on a novel ...
This study aims to present an Improved Type-2 Fuzzy Deep Learning (IT2FDL) framework for uncertainty management in character recognition using EEG signals by ...
Modeling uncertainty with evolutionary improved “fuzzy functions”. Celikyilmaz, Fethiye Asli. University of Toronto (Canada) ProQuest Dissertations & Theses ...
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Nov 21, 2024 · This chapter introduces a new uncertainty modeling architecture for the new improved fuzzy functions systems. The theory is based on a new ...
A three-phase development framework for fuzzy models is proposed by distinguishing between structural and parametric optimization processes, ...