An Intelligent Evaluation Method of Business English Translation Ability Based on Collaborative Game Particle Swarm Algorithm

Abstract

Abstract In today's globalized business climate, translation is essential for promoting successful communication. For precise and dependable communication, it is crucial to assess the translation skills of experts in the area of business English. However, the current evaluation techniques frequently lack clever and team-based methodologies to evaluate translation talents completely. In order to fill this gap, the Collaborative Game Particle Swarm Algorithm (CGPSA) is used in this study to present an intelligent evaluation approach for Business English translation proficiency. The CGPSA develops an interesting and efficient evaluation procedure by fusing the ideas of game theory and particle swarm optimization (PSO). The development of computerized sentence recognition that is specifically adapted to the features of business English has been greatly aided by the CGPSA. The CGPSA has been used to collect, organize, and analyze data, enabling sophisticated identification of business English. With a total score of 93.4, the suggested framework's results show high recognition accuracy. The findings show that in terms of accuracy in recognition, frequency magnitude, and intelligent translation, the CGPSA-based assessment technique performs better than conventional evaluation methodologies.