<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/559754B0-E18B-466F-8062-F8CC97A85528"><efrbr-work:titleOfTheWork>Neural networks in manufacturing cell design</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/559754B0-E18B-466F-8062-F8CC97A85528"><efrbr-expression:titleOfTheExpression>Neural networks in manufacturing cell design</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-11-07</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">1999</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>This paper presents a neural network approach in determining the appropriate manufacturing cell configuration that meets the required performance measures. Simulation experiments were conducted with many possible combinations of design changes to calculate cell performance measures, and thus generate training pairs for a neural network. Three different static neural network structures have been trained using the above data. Comparison of neural network efficiency and computational effort required is made through a case study, for every neural network architecture.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">Computers in Industry</efrbr-expression:note><efrbr-expression:note type="journal volume">36</efrbr-expression:note><efrbr-expression:note type="journal number">1-2</efrbr-expression:note><efrbr-expression:note type="page range">133-138</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~manolis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Christodoulou Manolis
            Χριστοδουλου Μανωλης
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            Gaganis Vasileios
            Γαγανης Βασιλειος
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            Elsevier
         </efrbr-corporateBody:nameOfTheCorporateBody></efrbr-corporateBody:corporateBody><efrbr-concept:concept identifier="http://id.loc.gov/authorities/subjects/sh90001937"><efrbr-concept:termForTheConcept>
            Artificial neural networks
            Nets, Neural (Computer science)
            Networks, Neural (Computer science)
            Neural nets (Computer science)
            neural networks computer science
            artificial neural networks
            nets neural computer science
            networks neural computer science
            neural nets computer science
         </efrbr-concept:termForTheConcept></efrbr-concept:concept><efrbr-concept:concept identifier="http://id.loc.gov/authorities/subjects/sh85107212"><efrbr-concept:termForTheConcept>
            Manufacturing engineering
            Process engineering
            production engineering
            manufacturing engineering
            process engineering
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