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Fuzzy similarity theory is used to evaluate the measurement uncertainty of automatic test system (ATS) used under a non-standard environment. Firstly, the automatic test system is verified in serials of environments, these verification environments are regarded as standard sample environments. Then by selecting proper similarity factors, the priority ratios between the non-standard environment and these standard sample environments are calculated, a similarity priority ratio matrix is established, and the similarity order numbers corresponding to each similarity factor are gained. Lastly, according to the weigh value of each similarity factor, the weighed similarity order numbers of each standard sample environment are calculated. The verification environment which has the minimum weighed similarity order number is the most similar sample to the non-standard environment. The verification result under this sample environment is regarded as the measurement uncertainty of the automatic test system used under the nonstandard environment.