The role of operational situation monitoring in English automatic translation equipment is very important, but there is a problem of inaccurate evaluation of results. The situational awareness algorithm cannot solve the problem of operational situation monitoring in English automatic translation equipment, and the evaluation is unreasonable. Therefore, this paper proposes an artificial intelligence algorithm for operation situation monitoring and analysis. Firstly, the data mining theory is used to evaluate the technology of English automatic translation equipment, and the indicators are divided according to the requirements of operation situation monitoring. Reduce interference factors in operational situation monitoring. Then, the data mining theory forms an operation situation monitoring scheme, and the operation situation monitoring results are comprehensively analyzed. FIONA shows that under the condition of certain evaluation standards, artificial intelligence algorithms monitor the accuracy and operation situation of operation situation Time outperforms situational awareness algorithms.

Data mining theory;Artificial intelligence algorithms;Operational situation monitoring;Situational awareness algorithms;English automatic translation equipment

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DOI： https://doi.org/10.62639/sspjinss03.20240102

Published： 2024