Retraction Note: Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books

Abstract

With the rapid development of social science and industrial technology, more and more attention has been paid to the evaluation of water environmental pollution. Bayesian network has strong probability theory inference ability, clear semantics, easy to understand, and other technical characteristics. This provides a natural and effective way to express dependency and causality, which can find potential relationships and patterns in datasets. Therefore, it has its own advantages in data mining. Bayesian network technology is used to study non-point source pollution in river basin and intelligent translation system of English books. Water pollution is one of the main problems that human beings are facing. In China, water pollution is more serious. First of all, the acceleration of urbanization and the change of land use will lead to the change of surface vegetation, resulting in the loss of soil and water. Secondly, many fertilizers, pesticides, and other chemical reagents are used in agricultural activities, some of which are absorbed by crops, and most of the rest are released from the soil in the process of rainfall. “Machine translation + post-translation editing” mode has been widely used in various translation projects, and the English Chinese subtitle translation project of “a little English” English learning software has adopted this mode. In practice, it is found that “machine translation + mode can improve the efficiency of subtitle E-C translation, but there are also limitations. In this paper, by analyzing the cases in the subtitle English-Chinese translation project of the English learning software, the advantages and typical errors of machine translation in subtitle English-Chinese translation are summarized, and the corresponding post-translation editing strategies are proposed for different error types. The main errors at the lexical level are the wrong choice of word meaning, no translation of abbreviations, and no translation of coined words. The proposed post-editing strategies are to locate polysemous words.