2008
DOI: 10.1080/10407790802483432
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Fuzzy Modeling of Performance of Counterflow Ranque-Hilsch Vortex Tubes with Different Geometric Constructions

Abstract: In this article, we present the development of a fuzzy expert system (FES) for fuzzy modeling of the performance of counterflow Ranque-Hilsch vortex tubes for different geometric constructions. Experimental values were obtained from a detailed experimental investigation. With these experimental values, FES models of the Ranque-Hilsch vortex tube behavior were designed using the MATLAB 6.5 fuzzy logic toolbox in Windows XP running on an Intel 3.0-Ghz PC. For this process P, N, n, and L/D were chosen as input an… Show more

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Cited by 26 publications
(8 citation statements)
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“…They are particularly useful in system modeling, such as in implementing complex mappings and system identification. AI systems comprise areas such as expert systems, artificial neural networks, genetic algorithms, fuzzy logic, and various hybrid systems, which combine two or more techniques (Kalogirou, 2003;Dincer et al, 2008). The aim of this article has been to show the possibility of the use of fuzzy logic for the calculation of performance HHO dry cell with different plate combination.…”
Section: Discussionmentioning
confidence: 99%
“…They are particularly useful in system modeling, such as in implementing complex mappings and system identification. AI systems comprise areas such as expert systems, artificial neural networks, genetic algorithms, fuzzy logic, and various hybrid systems, which combine two or more techniques (Kalogirou, 2003;Dincer et al, 2008). The aim of this article has been to show the possibility of the use of fuzzy logic for the calculation of performance HHO dry cell with different plate combination.…”
Section: Discussionmentioning
confidence: 99%
“…If C is the fuzzy set in question and C is integrable, then the defuzzified value of C by this method is Eq. 2, where [a, b] is an interval containing the support of C. This kind of defuzzification determines z* point as the middle of area (Nguyen et al 2003;Dincer et al 2008).…”
Section: Fuzzy Systemmentioning
confidence: 99%
“…where n is the number of data patterns, y p,m indicates the predicted, t m,m is the measured value of one data point m, and is the mean value of all measure data points [8]. Table 1.…”
Section: Artificial Neural Network (Ann)mentioning
confidence: 99%