Sky luminance data validation: Comparison of seven models with four data banks

Allocation models for DMUs with negative data

The formulas of cost and allocative efficiencies of decision making units (DMUs) with positive data cannot be used for DMUs with negative data. On the other hand, these formulas are needed to analyze the productivity and performance of DMUs with negative data. To this end, this study introduces the cost and allocative efficiencies of DMUs with negative data and demonstrates that the introduc...

New DEA/Location Models with Interval Data

Recently the concept of facility efficiency, which defined by data envelopment analysis (DEA), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. By combining the DEA models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

Building and Using Corporate Data Models: A Case Study of Four Australian Banks

A comparison between probabilistic and possibilistic models for data validation

Data validation for models with errors in the variables is an important aspect for supporting decision making. In this context, several concepts have been employed. In this paper, we compare a possiblistic and a probabilistic approach. The DuPont Business model is chosen as an example for a controlling model with errors. Although the FuzzyCalc algorithm, representing the possiblistic approach, ...

Linear Models for Functional Data

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