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- W3043282682 abstract "This paper presents a viable alternative solution for dominant point detection predicated on the comparison of suboptimal feature selection methods. Suboptimal feature selection methods are utilized as standard criteria to identify dominant points. Considering that all of the combinations of points comprise many sets, an algorithm that eliminates some of them is affirmed and illustrated. The sequential backward selection, sequential forward selection, generalized sequential forward selection, generalized sequential backward selection and plus l-take away r selection methods are performed on the remaining points to extract the dominant points. The simulation results exhibit that this method is significantly more effective and efficient in comparison to other proposed methods." @default.
- W3043282682 created "2020-07-23" @default.
- W3043282682 creator A5046578097 @default.
- W3043282682 date "2020-12-01" @default.
- W3043282682 modified "2023-10-13" @default.
- W3043282682 title "Dominant point detection based on suboptimal feature selection methods" @default.
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- W3043282682 doi "https://doi.org/10.1016/j.eswa.2020.113741" @default.
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