Intelligent English Translation and Optimization Based on Big Data Model

Abstract

With the development and popularization of communication technology, intelligent analysis using big data front-end in various fields is also skillful. In the study of English literature and short sentence translation, we should realize a fast and intelligent translation approach. Based on the analysis and research of big data, a set of online learning algorithms for English translation learning algorithms is compiled, which will greatly improve the efficiency and accuracy of translation. On the premise of online processing of big data English information, this paper shortens the processing time without affecting the translation accuracy. The radial function algorithm for big data reduces the complexity of big data, improves the computational efficiency of dealing with problems, and realizes the generalization of translation performance. The effective application of big data in the optimization practice of English translation will provide an effective theoretical way for accurate translation and realize intelligent model algorithm. The experimental results are summarized as follows: (1) with the increase of the number of translated texts, the translation time will also increase and the difficulty will increase. (2) The approximation value in radial basis function is used to evaluate the translation effect, and its error in 100 texts will decrease with the increase of literature, and its approximation state is consistent with the real state. (3) Among various translation techniques, conventional literal translation is still the usual method, and its feedback effect is also the best, which is the basic method of thinking according to data. (4) The evaluation of accuracy in intelligent calculation methods is different, from 100% accuracy under heterogeneous functions to 50% accuracy under unified algorithms, which shows that optimization methods need to be updated and improved in time.