Knowledge Resource Center for Ecological Environment in Arid Area
| DOI | 10.1007/s12517-021-07928-0 |
| Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books | |
| Weng, Tianyue | |
| 通讯作者 | Weng, TY (corresponding author), Hainan Coll Foreign Studies, Wenchang 571321, Hainan, Peoples R China. |
| 来源期刊 | ARABIAN JOURNAL OF GEOSCIENCES
 |
| ISSN | 1866-7511 |
| EISSN | 1866-7538 |
| 出版年 | 2021 |
| 卷号 | 14期号:16 |
| 英文摘要 | 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 + post-editing 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. |
| 英文关键词 | Bayesian network River basin Non-point source pollution English books Intelligent translation |
| 类型 | Article |
| 语种 | 英语 |
| 收录类别 | SCI-E |
| WOS记录号 | WOS:000679476900017 |
| WOS关键词 | EASTERN DESERT ; AREA ; GIS |
| WOS类目 | Geosciences, Multidisciplinary |
| WOS研究方向 | Geology |
| 资源类型 | 期刊论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/362561 |
| 作者单位 | [Weng, Tianyue] Hainan Coll Foreign Studies, Wenchang 571321, Hainan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Weng, Tianyue. Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books[J],2021,14(16). |
| APA | Weng, Tianyue.(2021).Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books.ARABIAN JOURNAL OF GEOSCIENCES,14(16). |
| MLA | Weng, Tianyue."Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books".ARABIAN JOURNAL OF GEOSCIENCES 14.16(2021). |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [Weng, Tianyue]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [Weng, Tianyue]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [Weng, Tianyue]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
