Neuro-fuzzy classification of the Rhagoletis pomonella species group using digitized wing structures
- Resource Type
- Conference
- Authors
- Bi, Chengpeng; Saunders, Michael C.; McPheron, Bruce A.
- Source
- 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology Computational Intelligence in Bioinformatics and Computational Biology, 2008. CIBCB '08. IEEE Symposium on. :159-165 Sep, 2008
- Subject
- Bioengineering
Computing and Processing
Fuzzy sets
Genetics
Artificial neural networks
Biological neural networks
Shape measurement
Veins
Fuzzy systems
Fuzzy neural networks
Bismuth
Area measurement
- Language
In this paper, we applied a neuro-fuzzy system to classify the morphologically indistinguishable Rhagoletis pomonella sibling species group. A carefully selected set of wing structure and shape variables were fuzzified using triangular membership functions. The neuro-fuzzy system NEFCLASS was applied to train the fly morphological datasets and a set of fuzzy rules were constructed. A fuzzy inference engine was constructed using the fuzzy rule bases. Furthermore, manually pruned fuzzy rules were employed to make a fuzzy key to classify this sibling species group.