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Classification of escherichia coli bacteria by artificial neural networks

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dc.contributor.authorAvci, M
dc.contributor.authorYildirim, W
dc.contributor.institutionauthorYILDIRIM, Tülay
dc.date.accessioned2026-06-27T12:57:09Z
dc.date.issued2002
dc.description.abstractThrough this paper, four different neural network structure which are multi layer perceptron, radial basis function, general regression neural network and probabilistic neural network were applied to the escherichia coli bacteria benchmark and most efficient neural network architecture for this data has been obtained. Better classification accuracy than the reference work using ad hoc structured probability model was achieved by probabilistic neural network.en
dc.identifier.endpage16
dc.identifier.isbn0-7803-7603-X
dc.identifier.startpage13
dc.identifier.urihttps://hdl.handle.net/20.500.14981/48085
dc.identifier.wos000180818100003
dc.language.isoeng
dc.publisherIEEE
dc.relation.conference1st International IEEE Symposium on Intelligent Systems
dc.relation.ispartof2002 FIRST INTERNATIONAL IEEE SYMPOSIUM INTELLIGENT SYSTEMS, VOL III, STUDENT SESSION, PROCEEDINGS
dc.subjectBack propagation
dc.subjectescherichia coli data
dc.subjectgeneral regression neural network
dc.subjectmulti layer perceptron
dc.subjectprobabilistic neural network
dc.subjectradial basis function
dc.subjectPROTEIN LOCALIZATION SITES
dc.subjectAutomation & Control Systems
dc.subjectComputer Science
dc.titleClassification of escherichia coli bacteria by artificial neural networks
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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