A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case
► The proposed Fuzzy-DELPHI method is developed to improve accuracy in adjustment of statistical forecasts. ► The limitations of the statistical extrapolation and the impact of sentiments are discussed. ► The Fuzzy-DELPHI is compared with the conventional ARIMA-GARCH framework and also with the base...
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| Published in | Expert systems with applications Vol. 39; no. 1; pp. 840 - 848 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4174 1873-6793 |
| DOI | 10.1016/j.eswa.2011.07.082 |
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| Abstract | ► The proposed Fuzzy-DELPHI method is developed to improve accuracy in adjustment of statistical forecasts. ► The limitations of the statistical extrapolation and the impact of sentiments are discussed. ► The Fuzzy-DELPHI is compared with the conventional ARIMA-GARCH framework and also with the base forecast of Naïve process.
This paper investigates the forecasting accuracy of fuzzy extended group decisions in the adjustment of statistical benchmark results. DELPHI is a frequently used method for implementing accurate group consensus decisions. The concept of consensus is subject to expert characteristics and it is sometimes ensured by a facilitator’s judgment. Fuzzy set theory deals with uncertain environments and has been adapted for DELPHI, called fuzzy-DELPHI (FD). The present paper extends the recent literature via an implementation of FD for the adjustment of statistical predictions. We propose a fuzzy-DELPHI adjustment process for improvement of accuracy and introduced an empirical study to illustrate its performance in the validation of adjustments of statistical forecasts in the dry bulk shipping index. |
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| AbstractList | This paper investigates the forecasting accuracy of fuzzy extended group decisions in the adjustment of statistical benchmark results. DELPHI is a frequently used method for implementing accurate group consensus decisions. The concept of consensus is subject to expert characteristics and it is sometimes ensured by a facilitator's judgment. Fuzzy set theory deals with uncertain environments and has been adapted for DELPHI, called fuzzy-DELPHI (FD). The present paper extends the recent literature via an implementation of FD for the adjustment of statistical predictions. We propose a fuzzy-DELPHI adjustment process for improvement of accuracy and introduced an empirical study to illustrate its performance in the validation of adjustments of statistical forecasts in the dry bulk shipping index. ► The proposed Fuzzy-DELPHI method is developed to improve accuracy in adjustment of statistical forecasts. ► The limitations of the statistical extrapolation and the impact of sentiments are discussed. ► The Fuzzy-DELPHI is compared with the conventional ARIMA-GARCH framework and also with the base forecast of Naïve process. This paper investigates the forecasting accuracy of fuzzy extended group decisions in the adjustment of statistical benchmark results. DELPHI is a frequently used method for implementing accurate group consensus decisions. The concept of consensus is subject to expert characteristics and it is sometimes ensured by a facilitator’s judgment. Fuzzy set theory deals with uncertain environments and has been adapted for DELPHI, called fuzzy-DELPHI (FD). The present paper extends the recent literature via an implementation of FD for the adjustment of statistical predictions. We propose a fuzzy-DELPHI adjustment process for improvement of accuracy and introduced an empirical study to illustrate its performance in the validation of adjustments of statistical forecasts in the dry bulk shipping index. |
| Author | Duru, Okan Bulut, Emrah Yoshida, Shigeru |
| Author_xml | – sequence: 1 givenname: Okan surname: Duru fullname: Duru, Okan email: duruokan@yahoo.com organization: Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla 34940, Istanbul, Turkey – sequence: 2 givenname: Emrah surname: Bulut fullname: Bulut, Emrah organization: Department of Maritime Logistics, Kobe University, Higashinada 658-0022, Kobe, Japan – sequence: 3 givenname: Shigeru surname: Yoshida fullname: Yoshida, Shigeru organization: Department of Maritime Logistics, Kobe University, Higashinada 658-0022, Kobe, Japan |
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| Keywords | Decision support systems Forecasting support systems Fuzzy-DELPHI Dry bulk shipping Consensus forecasts |
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| Snippet | ► The proposed Fuzzy-DELPHI method is developed to improve accuracy in adjustment of statistical forecasts. ► The limitations of the statistical extrapolation... This paper investigates the forecasting accuracy of fuzzy extended group decisions in the adjustment of statistical benchmark results. DELPHI is a frequently... |
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| SubjectTerms | Consensus forecasts Decision support systems Decisions Delphi Dry bulk shipping Drying Empirical analysis Forecasting support systems Fuzzy Fuzzy logic Fuzzy set theory Fuzzy-DELPHI Time series |
| Title | A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case |
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