An Improved Fuzzy Voting Scheme for Fault Tolerant Systems | IGI Global Scientific Publishing
An Improved Fuzzy Voting Scheme for Fault Tolerant Systems

An Improved Fuzzy Voting Scheme for Fault Tolerant Systems

Ram Murti Rawat (Indian Institute of Technology (BHU), Varanasi, India), Tarun Kumar Gupta (Jawaharlal Nehru University, New Delhi, India), Mohammad Sajid (Jawaharlal Nehru University, New Delhi, India), Shiv Prakash (Department of Chemical Engineering, Indian Institute of Technology, Delhi, India), Dinesh Prasad Sahu (School of Computer and systems Sciences, Jawaharlal Nehru University, New Delhi, India), Sohan Kumar Yadav (Jawaharlal Nehru University, New Delhi, India), and Chanchal Kumar (Jawaharlal Nehru University, New Delhi, India)
Copyright: © 2015 |Volume: 6 |Issue: 2 |Pages: 9
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466677500|DOI: 10.4018/IJAEC.2015040103
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MLA

Rawat, Ram Murti, et al. "An Improved Fuzzy Voting Scheme for Fault Tolerant Systems." IJAEC vol.6, no.2 2015: pp.41-49. https://doi.org/10.4018/IJAEC.2015040103

APA

Rawat, R. M., Gupta, T. K., Sajid, M., Prakash, S., Sahu, D. P., Yadav, S. K., & Kumar, C. (2015). An Improved Fuzzy Voting Scheme for Fault Tolerant Systems. International Journal of Applied Evolutionary Computation (IJAEC), 6(2), 41-49. https://doi.org/10.4018/IJAEC.2015040103

Chicago

Rawat, Ram Murti, et al. "An Improved Fuzzy Voting Scheme for Fault Tolerant Systems," International Journal of Applied Evolutionary Computation (IJAEC) 6, no.2: 41-49. https://doi.org/10.4018/IJAEC.2015040103

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Abstract

Voting is a widely used fault masking techniques for safety-critical systems to enhance the overall reliability of the system. Researchers over the period have proposed numerous advanced techniques in order to improve on the drawback of the existing methods. In this paper a fuzzy voting scheme has been survey and a generalized improved fuzzy voting scheme has been proposed. A comparative study of these schemes has also been carried out. It is found that proposed model is better than existing models. Single objective, multi-objective objective and many objective will be applied in future.

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