Abstract
With the rapid development of science and technology, more and more communication and exchanges are transmitting information through the network, which has higher and higher requirements for the difficulty of intelligent translation. On this basis, this article will specifically analyze the main factors that affect computer network information communication, take the computer network information intelligent translation as the starting point, and improve the level of information intelligent translation based on the combination of intelligent translation algorithms. Based on traditional algorithms, this paper can use high-strength artificial fish school algorithms to collect and process the data in the network more efficiently, so as to prevent errors in information translation. The intelligent translation algorithm model model studied in this paper mainly includes information collection and processing and more efficient and comprehensive translation of information. Through the analysis, it can be understood that the intelligent algorithm is to transform the key data and the key string. With the rapid development of big data technology, intelligent translation in computer network information can efficiently and accurately translate confidence. Experimental research results show that in the intelligent translation of computer network information, the use of artificial fish swarm algorithms can effectively improve the efficiency of information translation and the accuracy of translation results, and the speed and accuracy of traditional translation have doubled.
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Li, H. (2021). Big Data Technology in Intelligent Translation Algorithm in Computer Science. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-030-79197-1_45
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DOI: https://doi.org/10.1007/978-3-030-79197-1_45
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