[1]CHENG Linyan,HU Feng.Fuzzy hypernetwork-based knowledge acquisition method[J].CAAI Transactions on Intelligent Systems,2019,14(3):479-490.[doi:10.11992/tis.201804055]
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Fuzzy hypernetwork-based knowledge acquisition method
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 3
Page number:
479-490
Column:
学术论文—知识工程
Public date:
2019-05-05
- Title:
- Fuzzy hypernetwork-based knowledge acquisition method
- Keywords:
- fuzzy equivalence; fuzzy set; fuzzy rough set; three-way decision; hypernetworks; knowledge acquisition method; classification algorithm
- CLC:
- TP18
- DOI:
- 10.11992/tis.201804055
- Abstract:
- Combining the fuzzy rough set theory with the related knowledge on hypernetworks, this paper proposes a fuzzy hypernetwork mode. In comparison with the traditional hypernetwork model, the fuzzy hypernetwork model uses the fuzzy equivalence relationship to replace the distinct equivalence relation in hypernetworks and then improves the generation and evolution of hyperedges on this basis. First, the samples are divided into three regions according to their distribution:positive, boundary, and negative regions. The samples of different regions generate hyperedges in different ways. Second, the hyperedges are also divided into three regions according to their classification results, and the corresponding replacement of hyperedges in different regions is implemented. The experimental results show that the fuzzy hypernetwork classification algorithm presents prominent advantages in terms of accuracy, precision, and recall, thus proving the validity of the classification algorithm.
- References:
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1900-01-01