In this paper, a robust method, improved fuzzy classifier functions (IFCF) design is proposed for two-class pattern recognition problems. A supervised hybrid ...
In this paper, a robust method, improved fuzzy classifier functions (IFCF) design is proposed for two-class pattern recognition problems. A supervised hybrid ...
Celikyilmaz & I. B. Turksen, Increasing Accuracy of Two Class. Pattern Recognition with Improved Fuzzy Functions, Expert Systems with Applications, 36, pp. 1337 ...
From the results, the fuzzy-KNN achieved the best accuracy compared to the other adopted algorithms. Following that are the weighted-KNN then the KNN. The ...
Missing: Increasing enhanced
Oct 22, 2024 · In this state-of-the-art paper, we describe important advances of type-2 fuzzy sets for pattern recognition. Interests in type-2 fuzzy sets and ...
This could enable potential improvement of a recognition system. We have tested this methodology on a large set (30 398) of handwritten digit images. The method ...
Missing: enhanced | Show results with:enhanced
In this paper, we provide an in-depth review of popular methods for imbalanced databases related to patterns and fuzzy approaches.
Several researchers have proposed frameworks and design principles regarding the suitability of AISs as an adaptive soft computing paradigm and reviewed those.
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A review on type-2 fuzzy neural networks for system identification
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Mar 9, 2021 · T2F-NNs have high approximation accuracy, so these tools can be used wherever an accurate model is needed. Unlike to the T1F-NNs, the secondary ...
Aug 26, 2020 · Neuro-Fuzzy is one of the techniques commonly used in classification as it has been proven satisfactory in predicting results.