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

Authors:
Okan Duru;Emrah Bulut;Shigeru Yoshida
Affiliations:
Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla 34940, Istanbul, Turkey;Department of Maritime Logistics, Kobe University, Higashinada 658-0022, Kobe, Japan;Department of Maritime Logistics, Kobe University, Higashinada 658-0022, Kobe, Japan
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 5
Cited 0

The Max-Min Delphi method and fuzzy Delphi method via fuzzy integration

Fuzzy Sets and Systems
Forecasting enrollments with fuzzy time series—part I

Fuzzy Sets and Systems
Forecasting enrollments based on fuzzy time series

Fuzzy Sets and Systems
Six-Sigma project selection using national quality award criteria and Delphi fuzzy multiple criteria decision-making method

Expert Systems with Applications: An International Journal
The fuzzy Delphi method via fuzzy statistics and membership function fitting and an application to the human resources

Fuzzy Sets and Systems

Quantified Score

Hi-index	12.05

Visualization

Abstract

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.