Source: Computational Economics. Unidade: FEA
Subjects: PREVISÃO ECONÔMICA, TAXA DE CÂMBIO, ECONOMETRIA, FINANÇAS
ABNT
MACIEL, Leandro dos Santos; BALLINI, Rosangela. Functional fuzzy rule-based modeling for interval-valued data: an empirical application for exchange rates forecasting. Computational Economics, Dordrecht, v. 57, n. 2, p. 743-771, 2021. Disponível em: < https://link.springer.com/content/pdf/10.1007/s10614-020-09978-0.pdf > DOI: 10.1007/s10614-020-09978-0.APA
Maciel, L. dos S., & Ballini, R. (2021). Functional fuzzy rule-based modeling for interval-valued data: an empirical application for exchange rates forecasting. Computational Economics, 57( 2), 743-771. doi:10.1007/s10614-020-09978-0NLM
Maciel L dos S, Ballini R. Functional fuzzy rule-based modeling for interval-valued data: an empirical application for exchange rates forecasting [Internet]. Computational Economics. 2021 ; 57( 2): 743-771.Available from: https://link.springer.com/content/pdf/10.1007/s10614-020-09978-0.pdfVancouver
Maciel L dos S, Ballini R. Functional fuzzy rule-based modeling for interval-valued data: an empirical application for exchange rates forecasting [Internet]. Computational Economics. 2021 ; 57( 2): 743-771.Available from: https://link.springer.com/content/pdf/10.1007/s10614-020-09978-0.pdf