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• W2759783962 abstract "In this work, we consider the interval uncertainty from the probabilistic point of view, focusing on the establishment of probabilistic representation of interval uncertainty. A model-free sampling technique is first introduced, which can be used to produce a considerably larger sample from a given small sample. To make sure the local statistical characteristics of these two samples coincide, an improved model-free sampling technique is introduced based on probability weighted moments. The improved model-free sampling technique is then applied to obtain a large sample based on interval data, of which the probability distribution is produced by the kernel density estimator. Highest density regions based on estimated probability density function have been considered to further investigate the underlying information. The proposed probabilistic representation method is employed in the attempt of interval uncertainty propagation with the results compared with previous studies. The research adds a possible tool in the treatment of interval uncertainty." @default.
• W2759783962 created "2017-10-06" @default.
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• W2759783962 date "2018-06-05" @default.
• W2759783962 modified "2023-10-10" @default.
• W2759783962 title "A Probabilistic Representation Method for Interval Uncertainty" @default.
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• W2759783962 doi "https://doi.org/10.1142/s021987621850038x" @default.
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