Source: Computational Economics. Unidade: FEA
Subjects: FINANÇAS, PREVISÃO ECONÔMICA, TAXA DE CÂMBIO, ECONOMETRIA
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MACIEL, Leandro dos Santos e BALLINI, Rosangela. Functional fuzzy rule-based modeling for interval-valued data: an empirical application for exchange rates forecasting. Computational Economics, v. 57, n. 2, p. 743-771, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10614-020-09978-0. Acesso em: 18 ago. 2024.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.[citado 2024 ago. 18 ] Available from: https://doi.org/10.1007/s10614-020-09978-0Vancouver
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.[citado 2024 ago. 18 ] Available from: https://doi.org/10.1007/s10614-020-09978-0