In the construction of English teachers’ classroom competence system, traditional evaluation methods are incomplete in data collection, inaccurate in classification and insufficient in decision-making basis. Therefore, this paper introduced the K-means clustering algorithm in artificial intelligence algorithm to evaluate the English teaching ability. Based on the research of the K-means clustering algorithm and the implementation method, a fuzzy clustering algorithm combined with big data and information analysis is established to cluster various indicators in the English teaching ability system, which is the basis for improving teaching plan and evaluating teaching ability. It is proved by the simulation experiment that the evaluation of the English teaching ability is more accurate, and the scientific nature of the construction of the teaching ability system is effectively improved.

The study of competition pressure of athletes has been in the science circle for many years. However, computer science research as a coping strategy has not been involved in the past. Based on this, data mining was applied to the survey data of sports competition stress in this article. The basic theory of content-based recommendation algorithm was studied, including the idea of algorithm, algorithm description and algorithm implementation. Combining with the characteristics of the stressor data of sports competition, the algorithm was further improved from the perspective of similarity calculation and potential semantic analysis, and then the word frequency of the data was calculated to get the most similar suggestions, and the results obtained were analyzed.

With the gradual increase in the number of GNSS systems and the improvement of functions, in addition to the single-system navigation and timing service, the integrated navigation and positioning service among multiple systems can provide users with more accurate and stable positioning results, arousing more attention from the workers in GNSS field. Compatibility and interoperability among different systems has become a trend in the development of GNSS. Compatibility and interoperability between systems require a uniform time scale. Therefore, the measurement and forecasting of time deviations in GNSS systems is particularly important. This paper first studies the multi-system fusion location model and proposes an adaptive GNSS fusion PPP algorithm based on parameter equivalent reduction. Then, the method of fusion PPP is used to monitor the time difference of GNSS. Finally, the effectiveness of the improved algorithm and time difference monitoring method is verified by practical examples.