Because of the heavy competition and uncertainty in market conditions, attainment of complete and certain information flow becomes harder for businesses. In such environments, decision making with fuzzy data is rather important. Problems’ structures in practice are usually complicated and they...

The German meat market is facing considerable changes. Along with the boom of case-ready and discount stores, butchers and smaller retailers loose market shares, and private labels become widely accepted. The consumers' preferences are often neglected by these trends. This contribution discusses...

This paper develops a mathematicla programming model to reconcile trade statistics subject to a set of global consistency conditions in the presence of an entrepot. Initial data reliability serves a key function for governing the magnitude of adjustment. Through a two-stage optimization...

For the design of large and highly complex facilities – like, the international project ITER (http://www.iter.org/) – reliable basic data with well established covariance information (uncertainties, correlations) are indispensable. Procedures to attain the requirements by means of a Bayesian...

This paper addresses the issue of data quality in the real estate market. In many countries, the returns indices for direct markets are provided by several sources differing in terms of the methodology adopted and index weights. These differences produce a lack of informative standardisation,...

In many cases there is a need to balance commodity-flow system data quickly and with limited resources. In order to compile new supply and use tables and investment matrices consistent with revised national accounts data, it can be necessary to apply some sort of automatic balancing technique....

This paper presents an innovative fuzzy regression approach for the assessment of the potential vulnerability of bridge to earthquakes. Taking the Mao-Luo-Hsi Bridge in Nantou County of Taiwan as an example, structural models representing vulnerable sections of the bridge are established and...

In this article, we compare the forecasting performances of the Self-Exciting Threshold Autoregressive (SETAR) model and a fuzzy clustering regression model. The series used in this study are high-frequency financial data in the form of seven major stock prices in the US stock markets; the stock...

This paper introduces an integrated algorithm for forecasting electricity consumption (EL) based on fuzzy regression, time series and principal component analysis (PCA) in uncertain markets such as Iran. The algorithm is examined by mean absolute percentage error, analysis of variance (ANOVA)...