A comparison between probabilistic and possibilistic models for data validation
نویسنده
چکیده
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, and the SamPro algorithm, representing the probabilistic approach, use different calculi, their results are quite similar, proving themselves suitable for data validation.
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