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Fuzzy and neural approaches in engineering
Lefteri H. Tsoukalas,Robert E. Uhrig +1 more
- 01 Jan 1997
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TL;DR: Fuzzy and Neural Approaches in Engineering presents a detailed examination of the fundamentals of fuzzy systems and neural networks and then joins them synergistically - combining the feature extraction and modeling capabilities of the neural network with the representation capabilities of fuzzy Systems.
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Abstract: From the Publisher:
Fuzzy and Neural Approaches in Engineering presents a detailed examination of the fundamentals of fuzzy systems and neural networks and then joins them synergistically - combining the feature extraction and modeling capabilities of the neural network with the representation capabilities of fuzzy systems. Exploring the value of relating genetic algorithms and expert systems to fuzzy and neural technologies, this forward-thinking text highlights an entire range of dynamic possibilities within soft computing. With examples of specifically designed to illuminate key concepts and overcome the obstacles of notation and overly mathematical presentations often encountered in other sources, plus tables, figures, and an up-to-date bibliography, this unique work is both an important reference and a practical guide to neural networks and fuzzy systems.
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Citations
A Review Study on Mathematical Methods for Fault Detection Problems in Induction Motors
E. Ayaz
- 01 Sep 2014
TL;DR: In this article, the mathematical methods used in detection of mechanical and electrical faults of induction motors are reviewed together with theory and application examples on the current and vibration data which is acquired during performance tests of the motors followed by accelerated aging.
Genetic algorithm calibration of probabilistic cellular automata for modeling mining permit activity
Sushil J. Louis,Gary L. Raines +1 more
- 03 Nov 2003
TL;DR: Preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application and suggest that mineral resource information is a critical factor in the quality of the results.
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Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms
TL;DR: In this paper, the authors proposed a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks, which is coded by the GUI type using MATLAB.
6
Fuzzy-neural-network-based quality prediction system for sintering process
Jun Liao,Meng Jun Er,Jianya Lin +2 more
- 02 Jun 1999
TL;DR: A hybrid fuzzy neural networks (FNN) and genetic algorithm (GA) system is proposed to solve the difficult and challenging problem of constructing a system model from the given input and output data to predict the quality of chemical components of the finished sinter mineral.
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Appliance of recurrent neural network toward distance transmission lines protection
Anant Oonsivilai,Sanom Saichoomdee +1 more
- 01 Nov 2009
TL;DR: The appliance of recurrent neural network in transmission line protection is demonstrated and it is experiential that the proposed technique is competent to identify the particular fault direction more speedily and suitable for the realtime purposes.
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