Construction of International Education Talents Training Mechanism Based on Data Fusion Algorithm

Abstract

With the increasing trend of economic globalization and the continuous evolution of economic forms, the role of science and technology in promoting the development of human civilization has become more and more obvious. With the improvement of comprehensive national strength, the knowledge economy has brought new opportunities and challenges. With the increasing internationalization of higher education, it has not only driven the economic exchanges between countries but also led to the exchange of educational resources among transnational countries. However, China’s international education talent cultivation started late, with poor teaching awareness, imperfect discipline construction, and low quality of international education talents. A series of problems have seriously hindered the establishment of the talent training mechanism. In order to establish a reasonable and perfect talent training mechanism, optimize the international education talent training mechanism, make the international education talent training mechanism keep up with the development trend of science, technology, and education in the contemporary world, promote the internationalization of international education talent training, and strengthen the exchange of educational resources among countries. This paper uses various algorithms of fusion algorithms to accurately calculate the talent data. The algorithm results show that the optimized grouped quadratic combined Kalman filter has a shorter running time than the traditional Kalman filter, which decreased about 20%. The S-LEACH algorithm outperforms the traditional algorithm in the simulation results of the number of surviving nodes, relative energy consumption, and data transmission. In response to the national strategy of rejuvenating the country through science and education, cultivating international talents and building a modern talent training mechanism are particularly important.