Choosing a method for predicting economic performance of companies

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dc.contributor.author Dvořáček, Jaroslav
dc.contributor.author Sousedíková, Radmila
dc.contributor.author Řepka, Michal
dc.contributor.author Domaracká, Lucia
dc.contributor.author Barták, Pavel
dc.contributor.author Bartošíková, Michaela
dc.date.accessioned 2012-07-31T07:52:45Z
dc.date.available 2012-07-31T07:52:45Z
dc.date.issued 2012
dc.identifier.citation Metalurgija = Metallurgy. 2012, g. 51, br. 4, s. 525-528. cs
dc.identifier.issn 0543-5846
dc.identifier.issn 1334-2576
dc.identifier.uri http://hdl.handle.net/10084/94932
dc.identifier.uri 000305205800023
dc.description.abstract This paper reports on the eff orts to fi nd a method for predicting economic results of companies. The input data fi les consist of 93 profi table companies and 93 bankrupt fi rms. From the total number of 93 fi rms in both categories, data of 72 fi rms served for establishing a classifi cation criterion, and for the rest of 21 fi rms, a prognosis of their economic development was performed. The classifi cation criterion for prognosticating the future economic development has been established by applications of discriminate analysis, logit analysis, and artifi cial neural network methods. The application of artifi cial neural networks has provided for better classifi cation accuracies of 90,48 % for successful fi rms, and 100 % for bankrupt fi rms. cs
dc.format.extent 958112 bytes cs
dc.format.mimetype application/pdf cs
dc.language.iso en cs
dc.publisher Hrvatsko Metalurško Društvo cs
dc.relation.ispartofseries Metalurgija = Metallurgy cs
dc.relation.uri http://hrcak.srce.hr/file/123401 cs
dc.subject prediction cs
dc.subject discriminant analysis cs
dc.subject Logit analysis cs
dc.subject artificial neural networks cs
dc.subject classification accuracies cs
dc.subject predvidljivost cs
dc.subject analiza razlika cs
dc.subject analize logičke regresije (Logit analize) cs
dc.subject umjetne neuronske mreže cs
dc.subject klasifkacija točnosti cs
dc.title Choosing a method for predicting economic performance of companies cs
dc.title.alternative Izbor metode za predviđanje ekonomskih rezultata tvrtki cs
dc.type article cs
dc.identifier.location Není ve fondu ÚK cs
dc.description.abstract-en U ovom se članku opisuju pokušaji pronalaska učinkovite metode za predviđanje ekonomskog rezultata tvrtki. Datoteke ulaznih podataka sastoje se od 93 uspješne tvrtke i 93 tvrtke koje su bankrotirale. Od ukupnog broja od 93 tvrtke u obje kategorije datoteka s ulaznim podacima, podaci za 72 tvrtke poslužili su za određivanje klasifi kacijskog kriterija a za preostalu 21 tvrtku provela se prognoza njihovog ekonomskog razvoja. Klasifi kacijski kriterij za predviđanje budućeg ekonomskog razvoja tvrtke uspostavljen je primjenom analize diskriminacije, logičkom regresijom i metodama umjetne neuronske mreže. Primjena logičke regresije i umjetnih neuronskih mreža omogućila je bolju klasifi kacijsku točnost u slučaju 90,48 % uspješnih tvrtki i 100 % tvrtki koje su bankrotirale. cs
dc.rights.access openAccess cs
dc.type.version publishedVersion cs
dc.type.status Peer-reviewed cs
dc.description.source Web of Science cs
dc.description.volume 51 cs
dc.description.issue 4 cs
dc.description.lastpage 528 cs
dc.description.firstpage 525 cs
dc.identifier.wos 000305205800023

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