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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 Fuzzy PID Thermal Control System for Die Casting Processes
Tiebao Yang,Xiang Chen,Henry Hu +2 more
- 01 Oct 2007
TL;DR: The experimental results obtained from a laboratory die casting process simulator indicate that the developed control system is capable of adjusting the desired supply of cooling water into multiple cooling lines so that the local temperature distribution of the die insert may become more homogeneous.
8
A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration
TL;DR: A geospatial information system-assisted approach integrated with soft computing methods to manage spatial uncertainties during the hydrocarbon exploration process and the proposed hybrid method showed high predictive power and improved the quality of risk analysis.
8
Multioutput adaptive neuro-fuzzy inference system
T. Benmiloud
- 13 Jun 2010
TL;DR: To proves its performances, the proposed multi output ANFIS is used to make the approximation at the same time of three different functions of this neuro-fuzzy inference system.
8
Neural network modelling of creep in masonry
M. M. Reda Taha,Aboelmagd Noureldin,Naser El-Sheimy,Nigel G. Shrive +3 more
- 01 Aug 2004
TL;DR: In this article, a new method based on artificial intelligence to model creep of masonry is introduced, where feed-forward artificial neural networks (ANN) are investigated as a modelling technique for predicting creep.
8
New approach for automatic control modeling and analysis using Arithmetic And Visual Fuzzy Logic-based Representations in fully fuzzy environment
Hassen T. Dorrah,Walaa Ibrahim Gabr +1 more
- 20 Jun 2010
TL;DR: A new approach for the fuzzy modeling and analysis of automatic control systems in fully fuzzy environment based on the normalized fuzzy matrices and an extension of the Arithmetic and Visual Fuzzy Logic-based Representations developed recently by Gabr and Dorrah is presented.
8
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