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Estimating Probability of Gas Breakdown Using Grey-Fuzzy LogicCHEN, M.-J. , WU, Y.-C. , WEN, K.-L. , TSAI, M.-T.
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grey system theory, fuzzy theory, gas breakdown, probability estimation
grey(25), system(12), fuzzy(12), chen(7), systems(6), deng(6), control(5), applications(4)
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About this article
Date of Publication: 2013-08-31
Volume 13, Issue 3, Year 2013, On page(s): 113 - 120
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.03018
Web of Science Accession Number: 000326321600018
SCOPUS ID: 84884935729
Designing the protection system of high voltage power systems involves elucidating the properties of gas breakdown. This work presents a simplified mathematical approach based on grey and fuzzy methods to estimate the probability of gas breakdown, which differs from other grey-fuzzy methods. With the help of the data normalization process and a linear fuzzy membership function in determining the proper value of the distinguishing coefficient, the proposed approach outperforms other grey-fuzzy-based methods, the curve fitting method, and the neural network method in terms of estimation accuracy. The average relative error of test cases 1 and 2 with the normalization processing is 6.43%, which is 2.53 lower than that of the neural network method, 4.35% lower than that of the curve fitting method, 17.64 lower than that of the 5-interval max-max fuzzy-grey method, 1.51% lower than that of the 5-interval min-min fuzzy-grey method, 13.87% lower than that of the 3-interval max-max method, and 2.72% lower than that of the 3-interval min-min method.
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