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Study on the Intelligent Selection Model of Fuzzy Semantic Optimal Solution in the Process of Translation Using English Corpus
Wireless Communications and Mobile Computing Pub Date : 2020-09-08 , DOI: 10.1155/2020/8827657
Li Bei 1
Affiliation  

In order to improve the accuracy and reasonableness of using English corpus for translation, a method of using English corpus to perform translation tasks based on fuzzy semantic optimal solution intelligent selection and inspired computing for wireless networks is proposed. The information extraction model using English corpus for translation is constructed, and the fuzzy semantic keyword feature directivity model of English corpus translation is established. Fuzzy semantic ontology feature registration method is used to calculate the fuzzy semantic intelligence optimal solution vector in English translation. The semantic fuzzy feature matching and adaptive subject word registration are realized in English translation. The fuzzy link relation of semantic ontology is established, and the fuzzy semantic optimal solution is obtained. The accuracy of machine translation in English corpus is improved. The experimental results show that the fuzzy semantic optimal solution has better registration performance and the feature matching degree of the subject words is higher, which improves the reasonableness and accuracy of translation in English corpus. At the same time, it provides a new idea for intelligent computation and recognition of wireless network.

中文翻译:

英语语料库翻译过程中模糊语义最优解的智能选择模型研究

为了提高英语语料库翻译的准确性和合理性,提出了一种基于模糊语义最优解智能选择和启发式计算的英语语料库执行翻译任务的方法。建立了基于英语语料库的翻译信息提取模型,建立了英语语料库翻译的模糊语义关键词特征指向性模型。运用模糊语义本体特征注册方法计算了英语翻译中的模糊语义智能最优解向量。英文翻译实现了语义模糊特征匹配和自适应主题词注册。建立了语义本体的模糊联系关系,并获得了模糊语义最优解。提高了英语语料库中机器翻译的准确性。实验结果表明,模糊语义最优解具有更好的配准性能,主题词的特征匹配度更高,提高了英语语料库翻译的合理性和准确性。同时,它为无线网络的智能计算和识别提供了新思路。
更新日期:2020-09-08
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