首页|Data on Machine Learning Reported by Jhon Faber Marulanda Lopez and Colleagues ( Machine Learning Approach to Support Taxonomic Discrimination of Mayflies Specie s Based on Morphologic Data)
Data on Machine Learning Reported by Jhon Faber Marulanda Lopez and Colleagues ( Machine Learning Approach to Support Taxonomic Discrimination of Mayflies Specie s Based on Morphologic Data)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting from Vicosa, Brazil, by NewsR x journalists, research stated, "Artificial intelligence (AI) and machine learni ng (ML) offer objective solutions in the elaboration of taxonomic keys, such as the processing of large numbers of samples, aiding in the species identification , and optimizing the time required for this process. We utilized ML to study the morphological data of eight species of Americabaetis Kluge 1992, a diverse genu s in South American freshwater environments." The news correspondents obtained a quote from the research, "Decision trees were employed, examining specimens from the Museu de Entomologia da Universidade Fed eral de Vicosa (UFVB/Brazil) and literature data. Eleven morphological traits of taxonomic importance from the literature, including frontal keel, shape of the mouthparts, and abdominal color pattern, were analyzed. The decision tree obtain ed with the Gini algorithm effectively differentiates eight species (40% of the known species), using only eight morphological characters. Our analysis r evealed distinct groups within Americabaetis alphus Lugo-Ortiz and McCafferty 19 96a, based on variations in abdominal tracheae pigmentation. This study introduc es a novel approach,integrating AI techniques, biological collections, and lite rature data for aid in the Americabaetis species identification."
NETL
NSTL
