Spread factor in ranking fuzzy numbers
Ranking fuzzy numbers is one of the important element in solving decision making problems. Many approaches have been proposed in ranking fuzzy numbers. However, some of the proposed methods are rather limited to rank certain types of fuzzy numbers where two different fuzzy numbers is ranked equally....
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| creator | Hanif, H. M. Mohamad, D. Sulaiman, N. H. |
| description | Ranking fuzzy numbers is one of the important element in solving decision making problems. Many approaches have been proposed in ranking fuzzy numbers. However, some of the proposed methods are rather limited to rank certain types of fuzzy numbers where two different fuzzy numbers is ranked equally. For example two different embedded fuzzy numbers with the same midpoint and different symmetrical spread. In order to solve this matter, several researchers associated their method of ranking fuzzy numbers with spread factor. This paper reviews the spread factor in ranking fuzzy number by several researchers. A new spread calculation of fuzzy numbers will be proposed in this paper. Comparisons of size of spread for fuzzy numbers by other researchers' method with the proposed method will also be made to check on its consistency. Later, the implementation of spread factor in ranking fuzzy numbers is shown by implying the proposed method to two sets of fuzzy numbers. The proposed method is proven to be a better approach in solving the ranking problem of fuzzy numbers. |
| doi_str_mv | 10.1109/FSKD.2011.6019536 |
| format | Conference Proceeding |
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Comparisons of size of spread for fuzzy numbers by other researchers' method with the proposed method will also be made to check on its consistency. Later, the implementation of spread factor in ranking fuzzy numbers is shown by implying the proposed method to two sets of fuzzy numbers. 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M.</creatorcontrib><creatorcontrib>Mohamad, D.</creatorcontrib><creatorcontrib>Sulaiman, N. H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hanif, H. M.</au><au>Mohamad, D.</au><au>Sulaiman, N. H.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Spread factor in ranking fuzzy numbers</atitle><btitle>2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)</btitle><stitle>FSKD</stitle><date>2011-07</date><risdate>2011</risdate><volume>1</volume><spage>252</spage><epage>255</epage><pages>252-255</pages><isbn>9781612841809</isbn><isbn>1612841805</isbn><eisbn>9781612841816</eisbn><eisbn>1612841813</eisbn><eisbn>1612841791</eisbn><eisbn>9781612841793</eisbn><abstract>Ranking fuzzy numbers is one of the important element in solving decision making problems. Many approaches have been proposed in ranking fuzzy numbers. However, some of the proposed methods are rather limited to rank certain types of fuzzy numbers where two different fuzzy numbers is ranked equally. For example two different embedded fuzzy numbers with the same midpoint and different symmetrical spread. In order to solve this matter, several researchers associated their method of ranking fuzzy numbers with spread factor. This paper reviews the spread factor in ranking fuzzy number by several researchers. A new spread calculation of fuzzy numbers will be proposed in this paper. Comparisons of size of spread for fuzzy numbers by other researchers' method with the proposed method will also be made to check on its consistency. Later, the implementation of spread factor in ranking fuzzy numbers is shown by implying the proposed method to two sets of fuzzy numbers. The proposed method is proven to be a better approach in solving the ranking problem of fuzzy numbers.</abstract><pub>IEEE</pub><doi>10.1109/FSKD.2011.6019536</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011, Vol.1, p.252-255 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | a - cuts Computers Decision making Equations Indexes Mathematical model Ranking Fuzzy Numbers Risk analysis Spread |
| title | Spread factor in ranking fuzzy numbers |
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