A hybrid fuzzy/neural system used to extract heuristic knowledge from a fault detection problem

Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference ◽

10.1109/fuzzy.1994.343595 ◽

2002 ◽

Author(s):

P.V. Goode ◽

Mo-Yuen Chow

Keyword(s):

Fault Detection ◽

Neural System ◽

Detection Problem ◽

Heuristic Knowledge ◽

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Slip control of a quarter car model based on type-1 fuzzy neural system with parameterized conjunctions

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society ◽

10.1109/iecon.2012.6388857 ◽

2012 ◽

Author(s):

Ayse Cisel Aras ◽

Okyay Kaynak ◽

Rahib Abiyev

Keyword(s):

Neural System ◽

Slip Control ◽

Quarter Car Model ◽

Car Model ◽

Model Based ◽

Fuzzy Neural ◽

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Optimization of nonlinear characteristics of ball burnishing process using Sugeno fuzzy neural system

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1007/s40430-013-0060-8 ◽

2013 ◽

Vol 36 (1) ◽

pp. 101-109 ◽

Author(s):

M. R. Stalin John ◽

B. K. Vinayagam

Keyword(s):

Neural System ◽

Ball Burnishing ◽

Nonlinear Characteristics ◽

Fuzzy Neural ◽

Burnishing Process

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Model selection and fault detection approach based on Bayes decision theory: Application to changes detection problem in a distillation column

Process Safety and Environmental Protection ◽

10.1016/j.psep.2013.02.004 ◽

2014 ◽

Vol 92 (3) ◽

pp. 215-223 ◽

Author(s):

Yahya Chetouani

Keyword(s):

Model Selection ◽

Fault Detection ◽

Decision Theory ◽

Distillation Column ◽

Detection Problem ◽

Detection Approach ◽

Theory Application ◽

Changes Detection ◽

Bayes Decision Theory

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Fuzzy Neural Network based On-line Stator Winding Turn Fault Detection for Induction Motors

2007 2nd IEEE Conference on Industrial Electronics and Applications ◽

10.1109/iciea.2007.4318852 ◽

2007 ◽

Author(s):

Wang Xu-hong ◽

He Yi-gang

Keyword(s):

Neural Network ◽

Fault Detection ◽

Fuzzy Neural Network ◽

Induction Motors ◽

Stator Winding ◽

Fuzzy Neural ◽

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Optimal state space solution to the fault detection problem at DC

2010 Conference on Control and Fault-Tolerant Systems (SysTol) ◽

10.1109/systol.2010.5676039 ◽

2010 ◽

Author(s):

Ze Zhang ◽

M. Jaimoukha Imad

Keyword(s):

Fault Detection ◽

State Space ◽

Detection Problem ◽

Optimal State ◽

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Incipient Fault Detection and Diagnosis: A hidden information detection problem

2015 IEEE 24th International Symposium on Industrial Electronics (ISIE) ◽

10.1109/isie.2015.7281579 ◽

2015 ◽

Author(s):

Claude Delpha ◽

Demba Diallo

Keyword(s):

Fault Detection ◽

Fault Detection And Diagnosis ◽

Detection Problem ◽

Hidden Information ◽

Information Detection ◽

Incipient Fault ◽

Detection And Diagnosis ◽

Incipient Fault Detection

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Short term load forecasting using hybrid adaptive fuzzy neural system: The performance evaluation

2017 IEEE PES PowerAfrica ◽

10.1109/powerafrica.2017.7991270 ◽

2017 ◽

Author(s):

Daud Mustafa Minhas ◽

Raja Rehan Khalid ◽

Georg Frey

Keyword(s):

Performance Evaluation ◽

Load Forecasting ◽

Neural System ◽

Adaptive Fuzzy ◽

Short Term Load Forecasting ◽

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Fault detection of rotating machine parts using novel fuzzy neural network

IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028) ◽

10.1109/icsmc.1999.814118 ◽

2003 ◽

Author(s):

S. Taniguchi ◽

D. Akhmetov ◽

Y. Dote

Keyword(s):

Neural Network ◽

Fault Detection ◽

Fuzzy Neural Network ◽

Rotating Machine ◽

Fuzzy Neural ◽

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IT2-GSETSK: An evolving interval Type-II TSK fuzzy neural system for online modeling of noisy data

Neurocomputing ◽

10.1016/j.neucom.2020.03.065 ◽

2020 ◽

Vol 407 ◽

pp. 1-11

Author(s):

Mohammad Ashrafi ◽

Dilip K. Prasad ◽

Chai Quek

Keyword(s):

Neural System ◽

Type Ii ◽

Online Modeling ◽

Fuzzy Neural ◽

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A matrix factorization solution to the H-/H∞ fault detection problem

10.1016/j.automatica.2006.06.002 ◽

2006 ◽

Vol 42 (11) ◽

pp. 1907-1912 ◽

Author(s):

Imad M. Jaimoukha ◽

Zhenhai Li ◽

Vasilios Papakos

Keyword(s):

Fault Detection ◽

Matrix Factorization ◽

Detection Problem

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