Artificial Neural Networks; Definition, Properties and Misuses

dc.authorscopusid24922866200
dc.authorscopusid15765186400
dc.contributor.authorGuresen, E.
dc.contributor.authorKayakutlu, G.
dc.date.accessioned2024-10-15T20:23:23Z
dc.date.available2024-10-15T20:23:23Z
dc.date.issued2011
dc.departmentOkan Universityen_US
dc.department-tempGuresen E., Okan University, Department of Business Administration, Turkey; Kayakutlu G., Istanbul Technical University, Department of Industrial Engineering, Turkeyen_US
dc.description.abstractThere are no such clear and good definitions of ANNs in the literature. Many of the definitions refer to the figures instead of well explaining the ANNs. That is why many weighted graphs (as in shortest path problem networks) fit the definition of ANN. This study aims to give a clear definition that will differentiate ANN and graphs (or networks) by referring to biological neural networks. Although there is no input choice limitation or prior assumption in ANN, sometimes researchers compare ANN achievements with the results of other methods using different input data and make comments on these results. This study also gives examples from literature to misuses, unfair comparisons and evaluates the underlying reasons which will guide researchers. © 2011 Nova Science Publishers, Inc. All rights reserved.en_US
dc.identifier.citation0
dc.identifier.citationcount0
dc.identifier.endpage189en_US
dc.identifier.isbn9781613242858
dc.identifier.scopus2-s2.0-84892041768
dc.identifier.scopusqualityN/A
dc.identifier.startpage171en_US
dc.identifier.wosqualityN/A
dc.language.isoen
dc.language.isoenen_US
dc.publisherNova Science Publishers, Inc.en_US
dc.relation.ispartofFocus on Artificial Neural Networksen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.scopus.citedbyCount0
dc.titleArtificial Neural Networks; Definition, Properties and Misusesen_US
dc.typeBook Parten_US
dspace.entity.typePublication

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