Tourism English Translation System Based on Fuzzy Clustering Algorithm

With the rapid development of economic globalization and the Internet, international exchanges and cooperation have become increasingly extensive and in-depth. Language differences have become the biggest obstacle to international communication and cooperation. The main research of this paper is the tourism English translation system based on fuzzy clustering algorithm. This system uses black box testing to test and verify system functions. Performance indicators mainly include response time, throughput, and so on. Complete the performance test of the system by checking the monitoring points in the performance test cases. To confirm whether the basic performance requirements of the system are met, performance testing is very important. In this teaching system, the response time and throughput of the system are mainly tested. In the system performance test cases, the use cases are divided according to the number of online users, and the response time of the client is tested in each use case. If the indicator requirements are met, the use case is deemed qualified, otherwise it is unqualified, and the system defects are recorded according to the actual test structure. The data shows that the correct clustering data of C-FCA is further improved to 95% based on the better PCM algorithm. The results show that the fuzzy clustering algorithm can effectively improve the accuracy of the tourism English translation system.