Roughness and similarity measure of rough neutrosophic multisets using vectorial model of information
The roughness and similarity measure for two different information in the same universal set is useful in explaining the strength and completeness of the information given. Then, for rough neutrosophic multisets environment, the lower and upper approximation was a concerned property to study in e...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2020
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| Online Access: | http://journalarticle.ukm.my/16071/1/jqma-16-2-paper7-2.pdf http://journalarticle.ukm.my/16071/ https://www.ukm.my/jqma/current/ |
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| Summary: | The roughness and similarity measure for two different information in the same universal set is
useful in explaining the strength and completeness of the information given. Then, for rough
neutrosophic multisets environment, the lower and upper approximation was a concerned
property to study in explaining the roughness of the information needed. Meanwhile, the
vectorial models of information which are cosine measure and dice measure represent the result
for the similarity measure of rough neutrosophic multisets. The finding of this set theory gives
a new generalization about similarity measure for multiple information involving indeterminacy
information in the same environment. Besides that, the rough neutrosophic multisets theory also
applicable set-in decision making for medical diagnosis. The comparison result showed that the
roughness approximation of information is essential to get the best result in a close similarity
measure. |
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