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001439517 001__ 1439517
001439517 003__ OCoLC
001439517 005__ 20230309004432.0
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001439517 020__ $$a9783030756499$$q(electronic bk.)
001439517 020__ $$a3030756491$$q(electronic bk.)
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001439517 0247_ $$a10.1007/978-3-030-75649-9$$2doi
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001439517 049__ $$aISEA
001439517 050_4 $$aQA280$$b.V73 2021
001439517 08204 $$a519.5/5$$223
001439517 1001_ $$aVrbka, Jaromír,$$eauthor.
001439517 24510 $$aUsing artificial neural networks for timeseries smoothing and forecasting :$$bcase studies in economics /$$cJaromír Vrbka.
001439517 264_1 $$aCham :$$bSpringer,$$c[2021]
001439517 264_4 $$c©2021
001439517 300__ $$a1 online resource :$$billustrations (chiefly color)
001439517 336__ $$atext$$btxt$$2rdacontent
001439517 337__ $$acomputer$$bc$$2rdamedia
001439517 338__ $$aonline resource$$bcr$$2rdacarrier
001439517 347__ $$atext file
001439517 347__ $$bPDF
001439517 4901_ $$aStudies in computational intelligence,$$x1860-9503 ;$$vvolume 979
001439517 504__ $$aIncludes bibliographical references.
001439517 5050_ $$aTime series and their importance to the economy -- Econometrics- selected models -- Artificial neural networks- selected models -- Comparison of different methods -- Conclusion.
001439517 506__ $$aAccess limited to authorized users.
001439517 520__ $$aThe aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.
001439517 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 17, 2021).
001439517 650_0 $$aTime-series analysis.
001439517 650_0 $$aNeural networks (Computer science)
001439517 650_0 $$aGold$$xPrices$$xForecasting.
001439517 650_6 $$aSérie chronologique.
001439517 650_6 $$aRéseaux neuronaux (Informatique)
001439517 650_6 $$aOr$$xPrix$$xPrévision.
001439517 655_0 $$aElectronic books.
001439517 77608 $$iPrint version:$$z3030756483$$z9783030756482$$w(OCoLC)1245656491
001439517 830_0 $$aStudies in computational intelligence ;$$vv. 979.$$x1860-9503
001439517 852__ $$bebk
001439517 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-75649-9$$zOnline Access$$91397441.1
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001439517 980__ $$aEBOOK
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001439517 983__ $$aOnline
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