Results 1 to 10 of about 52,378 (250)
ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers [PDF]
Open Engineering, 2016 In this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS.
César Manuel Braz, Barros Rui Carneiro
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Flexible neuro-fuzzy systems [PDF]
IEEE Transactions on Neural Networks, 2003 In this paper, we derive new neuro-fuzzy structures called flexible neuro-fuzzy inference systems or FLEXNFIS. Based on the input-output data, we learn not only the parameters of the membership functions but also the type of the systems (Mamdani or logical). Moreover, we introduce: 1) softness to fuzzy implication operators, to aggregation of rules and
L, Rutkowski, K, Cpalka
exaly +6 more sources
TASK Quarterly, 2003 In this paper we present the Beta function and its main properties. A key feature of the Beta function, which is given by the central limit theorem, is also shown.
ADEL M. ALIMI
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Scientific African, 2023 Purpose: Neuro-fuzzy systems aim to combine the benefits of artificial neural networks and fuzzy inference systems: a neural network can learn patterns from data and achieves high performance, whereas a fuzzy system matches inputs and outputs using ...
Hafsaa Ouifak, Ali Idri
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An indirect adaptive neuro-fuzzy speed control of induction motors [PDF]
Journal of Artificial Intelligence and Data Mining, 2016 This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and ...
M. Vahedi +2 more
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Using an adaptive fuzzy-logic system to optimize the performances and the reduction of chattering phenomenon in the control of induction motor [PDF]
Serbian Journal of Electrical Engineering, 2009 Neural networks and fuzzy inference systems are becoming well recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance.
Barazane Linda +3 more
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Study the Robustness of Automatic Voltage Regulator for Synchronous Generator Based on Neuro-Fuzzy Network [PDF]
Engineering and Technology Journal, 2015 Modern power systems are complex and non-linear and their operating conditions can vary over a wide range, and since neuro - fuzzy networkcan be used as intelligent controllers to control non-linear dynamic systems through learning, which can easily ...
Abdulrahim Thiab Humod +1 more
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Performance of heterogenous neuro-fuzzy ensembles over medical datasets
Scientific African, 2023 Neuro-fuzzy systems combine the abilities of both artificial neural networks and fuzzy systems. They are easily trainable and provide a certain level of interpretability.
Hicham Benbriqa +2 more
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Design and Optimization of a Neuro-Fuzzy System for the Control of an Electromechanical Plant
Applied Sciences, 2022 One characteristic of neuro-fuzzy systems is the possibility of incorporating preliminary information in their structure as well as being able to establish an initial configuration to carry out the training.
Helbert Espitia +2 more
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WRNFS: Width Residual Neuro Fuzzy System, a Fast-Learning Algorithm with High Interpretability
Applied Sciences, 2022 Although the deep neural network has a strong fitting ability, it is difficult to be applied to safety-critical fields because of its poor interpretability. Based on the adaptive neuro-fuzzy inference system (ANFIS) and the concept of residual network, a
Lingkun Kong, Dewang Chen, Ruijun Cheng
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