Combining Interval, Probabilistic, and Fuzzy Uncertainty: Foundations, Algorithms, Challenges – An Overview
نویسندگان
چکیده
Probabilistic and . . . Interval . . . Why Not Maximum . . . Chip Design: Case . . . General Approach: . . . Interval Approach: . . . Extension of Interval . . . Successes (cont-d) Challenges Problem Main Idea: Use Moments Formulation of the . . . Result Case Study: . . . General Problem Case Study: Detecting . . . Outlier Detection . . . Outlier Detection . . . Fuzzy Uncertainty: In . . . Acknowledgments Detecting Possible . . . Computing Lower . . . Computing Upper . . . Computational . . . How Can We Actually . . . Computing Upper . . . Computing Lower . . .
منابع مشابه
Combining Interval and Probabilistic Uncertainty: Foundations, Algorithms, Challenges – An Overview
Since the 1960s, many algorithms have been designed to deal with interval uncertainty. In the last decade, there has been a lot of progress in extending these algorithms to the case when we have a combination of interval and probabilistic uncertainty. We provide an overview of related algorithms, results, and remaining open problems.
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