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This article presents a new class of expected model (UDEA model for short) about data envelopment analysis (DEA) in uncertainty environments,in which the inputs and outputs are assumed to be characterized by uncertain variables with known distributions.When the inputs and outputs are mutually independent special variables,we can turn the uncertain constraints and the expected objective into their equivalent stochastic ones by applying the established formulas for the uncertain distributions.Finally,one numerical example is presented to demonstrate the proposed modeling idea and the efficiency in the proposed model.