Name
Abstract | ||
|---|---|---|
Rough set theory and neutrosophic set theory are mathematical models to deal with incomplete and vague information. These two theories can be combined into a framework for modeling and processing incomplete information in information systems. Thus, the neutrosophic rough set hybrid model gives more precision, flexibility and compatibility to the system as compared to the classic and fuzzy models. In this research study, we develop neutrosophic rough digraphs based on the neutrosophic rough hybrid model. Moreover, we discuss regular neutrosophic rough digraphs, and we solve decision-making problems by using our proposed hybrid model. Finally, we give a comparison analysis of two hybrid models, namely, neutrosophic rough digraphs and rough neutrosophic digraphs. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/a11050059 | ALGORITHMS |
Keywords | Field | DocType |
neutrosophic rough hybrid model,regular neutrosophic rough digraphs,decision-making method | Information system,Fuzzy logic,Rough set,Artificial intelligence,Mathematical model,Machine learning,Mathematics,Complete information,Neutrosophic set | Journal |
Volume | Issue | ISSN |
11 | 5 | 1999-4893 |
Citations | PageRank | References |
2 | 0.37 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Akram | 1 | 365 | 54.94 |
| Nabeela Ishfaq | 2 | 2 | 0.71 |
| Sidra Sayed | 3 | 2 | 1.04 |
| Florentin Smarandache | 4 | 728 | 104.92 |