Search Results - "Plurality (voting)"

Exact parallel plurality voting algorithm for totally ordered object space fault-tolerant systems by Karimi, Abbas, Zarafshan, Faraneh, Jantan, Adznan, Ramli, Abdul Rahman, Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad

“…Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, they are therefore used to achieve a new parallel plurality voting algorithm by using (n/log n) processors on EREW shared-memory PRAM. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. Since Plurality voting, among the popular and widely applied algorithms, has more correct responses even more than the most known and practical voting algorithm like majority and by relying on the benefit of parallel algorithms, we proposed parallel plurality voting with the minimum number of processors in an optimal time compared to its sequential type. …”
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Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP by Loo, C.K., Rao, M.V.C.

“…In this paper, an accurate and effective probabilistic plurality voting method to combine outputs from multiple Simplified Fuzzy ARTMAP (SFAM) classifiers is presented. …”
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Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation by Loo, Chu Kiong, Law, Augustine, Lim, W. S., Rao, M. V. C.

“…The PESFAM implements an accurate and effective probabilistic plurality voting method to combine outputs from multiple SFAM classifiers. …”
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Improving super-resolution mapping through combining multiple super-resolution land-cover maps by Li, Xiaodong, Ling, Feng, Foody, Giles M., Du, Yun

“…A multiple SRM (M-SRM) method that combines the sub-pixel maps obtained from a set of SRM analyses, obtained from a single or multiple set of algorithms, is proposed in this study. Plurality voting, which selects the class with the most votes, is used to label each sub-pixel. …”
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