A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case

• Published in: Expert systems with applications Vol. 39; no. 1; pp. 840 - 848
• Main Authors: Duru, Okan, Bulut, Emrah, Yoshida, Shigeru
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2012
• Subjects: 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; Decision support systems; Forecasting support systems; Fuzzy-DELPHI; Dry bulk shipping; Consensus forecasts
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2011.07.082

► 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.