Name
Title | ||
|---|---|---|
Fuzzy approach for classification of pork into quality grades: coping with unclassifiable samples. |
Abstract | ||
|---|---|---|
•Fuzzy solution is better than traditional method to classify pork into quality grades.•The fuzzy logic are able to handle infeasible samples in classification.•The fuzzy logic enables the industry to meet specific market requirements.•It was possible to detect the contribution of pH in infeasible samples composition. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compag.2018.05.009 | Computers and Electronics in Agriculture |
Keywords | Field | DocType |
Classical logic,Classification,Computational intelligence,Fuzzy Logic,Meat,Pattern recognition | Statistical difference,Computer vision,Coping (psychology),Fuzzy logic,Artificial intelligence,Engineering,Ambiguity,Machine learning | Journal |
Volume | ISSN | Citations |
150 | 0168-1699 | 1 |
PageRank | References | Authors |
0.63 | 5 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Louise Manha Peres | 1 | 1 | 0.63 |
| Sylvio Barbon | 2 | 46 | 10.97 |
| Estefânia Mayumi Fuzyi | 3 | 1 | 0.63 |
| Ana Paula A. C. Barbon | 4 | 1 | 0.63 |
| Douglas Fernandes Barbin | 5 | 5 | 1.72 |
| Priscila Tiemi Maeda Saito | 6 | 1 | 0.63 |
| Nayara Andreo | 7 | 1 | 0.63 |
| Ana Maria Bridi | 8 | 6 | 1.24 |