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

被引：53

作者：

Duru, Okan ^{[1
]}

Bulut, Emrah ^{[2
]}

Yoshida, Shigeru ^{[2
]}

机构：

[1] Istanbul Tech Univ, Dept Maritime Transportat & Management Engn, TR-34940 Istanbul, Turkey

[2] Kobe Univ, Dept Maritime Logist, Kobe, Hyogo 6580022, Japan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 01期

关键词：

Fuzzy-DELPHI; Decision support systems; Forecasting support systems; Dry bulk shipping; Consensus forecasts; FORECASTING ENROLLMENTS; LIKELIHOOD;

D O I：

10.1016/j.eswa.2011.07.082

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：840 / 848

页数：9

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