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FuBiNFS – fuzzy biclustering neuro-fuzzy system

Fuzzy Sets and Systems, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Rough set-based neuro-fuzzy system

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
Neuro-fuzzy hybridization is the oldest and most popular methodology in soft computing (Mitra & Hayashi, 2000). Neuro-fuzzy hybridization is known as Fuzzy Neural Networks, or Neuro-Fuzzy Systems (NFS) in the literature (Lin & Lee, 1996; Mitra & Hayashi, 2000).
null Kai Keng Ang, null Chai Quek
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Neuro-Fuzzy Systems

1998
This paper is about so-called neuro-fuzzy systems, which combine methods from neural network theory with fuzzy systems. Such combinations have been considered for several years already. However, the term neuro-fuzzy still lacks proper definition, and still has the flavour of a buzzword to it.
Rudolf Kruse, Detlef Nauck
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NEURO-FUZZY STRUCTURES IN FDI SYSTEM

IFAC Proceedings Volumes, 2002
Abstract Fault diagnosis systems have an important role in industrial plants because the early fault detection and isolation (FDI) can minimize damages in the plants. The main aim of this work is to propose a two-stage neuro-fuzzy approach as a fault diagnosis system in dynamic processes.
Mendes, Mário J. G. C.   +3 more
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Adaptive Neuro-Fuzzy Systems

2009
Fuzzy logic became the core of a different approach to computing. Whereas traditional approaches to computing were precise, or hard edged, fuzzy logic allowed for the possibility of a less precise or softer approach (Klir et al., 1995, pp. 212-242). An approach where precision is not paramount is not only closer to the way humans thought, but may be in
Larbi Esmahi   +2 more
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Neuro-fuzzy systems in medicine

2010 11th International Symposium on Computational Intelligence and Informatics (CINTI), 2010
Neuro-fuzzy systems are widely used in both applied and experimental medicine and are one of the most modern subjects of today's Medical Informatics. Despite the initial refuse of their use due to informatical, economical, educational and other reasons, these systems are widely accepted in medical institutions operating in all levels of healthcare. The
Andor Sagi   +3 more
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Superior neuro-fuzzy classification systems

Neural Computing and Applications, 2012
Although adaptive neuro-fuzzy inference system (ANFIS) has very fast convergence time, it is not suitable for classification problems because its outputs are not integer. In order to overcome this problem, this paper provides four adaptive neuro-fuzzy classifiers; adaptive neuro-fuzzy classifier with linguistic hedges (ANFCLH), linguistic hedges neuro ...
Ahmad Taher Azar, Shaimaa Ahmed El-Said
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Hierarchical Neuro-Fuzzy Systems Part I

2009
Neuro-fuzzy [Jang,1997][Abraham,2005] are hybrid systems that combine the learning capacity of neural nets [Haykin,1999] with the linguistic interpretation of fuzzy inference systems [Ross,2004]. These systems have been evaluated quite intensively in machine learning tasks.
Marley Vellasco   +3 more
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Neuro-fuzzy systems

The neuro-fuzzy system has gotten the great attention of researchers in numerous scientific areas due to its practical reasoning and learning capabilities. This chapter aims to help researchers to get a brief overview of the fuzzy sets and the related operations.
Zeinalnezhad, Masoomeh   +2 more
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Hierarchical Neuro-Fuzzy Systems

2003
Robot audition in the real world should cope with environment noises and reverberation and motor noises caused by the robot's own movements. This paper presents the active direction-pass filter (ADPF) to separate sounds originating from the specified direction with a pair of microphones. The ADPF is implemented by hierarchical integration of visual and
M. Vellasco, M. Pacheco, K. Figueiredo
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