Design and Implementation of Fuzzy Expert System Based on Evolutionary Algorithms for Diagnosing the Intensity Rate of Hepatitis C-Reference-Cited by-同舟云学术

Design and Implementation of Fuzzy Expert System Based on Evolutionary Algorithms for Diagnosing the Intensity Rate of Hepatitis C

Published:2018 Issue: Volume: Page:24-36
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Behrooz Mehrnaz,Zarandi Mohammad Hossein Fazel

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-95312-0_3

Reference23 articles.

1. Modi, A.A., Liang, T.J.: Hepatitis C: a clinical review. Oral Dis. 14(1), 10–14 (2008)

2. Patterson, D.: Introduction to Artificial Intelligence and Expert Systems. Prentice-Hall Inc., Upper Saddle River (1990)

3. Hasan, M.A., Chowdhury, A.R.: Human disease diagnosis using a fuzzy expert system. arXiv preprint arXiv:1006.4544 (2010)

4. Neshat, M., Yaghobi, M.: Designing a fuzzy expert system of diagnosing the hepatitis B intensity rate and comparing it with adaptive neural network fuzzy system. In: Proceedings of the World Congress on Engineering and Computer Science, vol. 2, pp. 797–802, October 2009

5. Sotudian, S., Zarandi, M.F., Turksen, I.B.: From Type-I to Type-II fuzzy system modeling for diagnosis of hepatitis. World Acad. Sci. Eng. Technol. Int. J. Comput. Electr. Autom. Control Inf. Eng. 10(7), 1280–1288 (2016)

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