Research on the Application of Gray Prediction and BP Neural Network in English-Chinese Translation Quality Assessment

[1] Petersen, M. (2017). Translation and quality management: some implications for the theory, practice and teaching of translation. Philosophical Explorations, 9(16), 201. Search in Google Scholar

[2] Deng, D., & Xue, N. (2017). Translation divergences in chinese–english machine translation: an empirical investigation. Computational Linguistics, 1–65. Search in Google Scholar

[3] Hossein Nassaji. (2017). Language instruction and language acquisition: a complex interplay:. Language Teaching Research, 21(5), 543–545. Search in Google Scholar

[4] Miriam Buendía Castro. (2019). Bilingual and multilingual online environmental knowledge resources: a comparative study for translation purposes. International Journal of Lexicography(2). Search in Google Scholar

[5] Afreen, A. (2023). Translator identity and the development of multilingual resources for language learning. TESOL Quarterly, 57(1), 90–114. Search in Google Scholar

[6] Hosseini, S., Tajvidi, G. R., & Kerremans, K. (2019). Social constructivism in translator education: the stakeholders’ needs assessment. Translation Studies. Search in Google Scholar

[7] Frank, S., Elliott, D., & Specia, L. (2018). Assessing multilingual multimodal image description: studies of native speaker preferences and translator choices. Natural Language Engineering, 24(pt.3), 393–413. Search in Google Scholar

[8] Luca, Mauri, Andrea, Vallati, Pawel, & Ocoń. (2018). International germplasm exchanges are getting more complicated, and here’s why that matters to global food security. Journal of Cleaner Production. Search in Google Scholar

[9] Rajesh, S., Shivangi, T., Rohit, V., & Manjari, T. (2024). Translation and adaptation of cognistat in hindi language: for computerized evaluation of cognitive functioning. Archives of Clinical Neuropsychology. Search in Google Scholar

[10] Soo, R., & Monahan, P. J. (2021). Language dominance affects auditory translation priming in heritage speakers. The Journal of the Acoustical Society of America, 150(4), A44–A44. Search in Google Scholar

[11] Uman, S., Jakupovi, A., & Marinac, M. (2020). A dictionary for translation from natural to formal data model language. Computational Intelligence. Search in Google Scholar

[12] Xiao, Y., Zhang, K., Xu, M., & Liu, Y. (2018). A social topn recommendation scheme based on grey forecast model. Journal of Grey System, 30(4), 78–96. Search in Google Scholar

[13] Hajek, P., Froelich, W., & Prochazka, O. (2020). Intuitionistic fuzzy grey cognitive maps for forecasting interval-valued time series. Neurocomputing(Aug.4), 400. Search in Google Scholar

[14] Liu, L., Peng, Q., Jiang, H., Ran, L., Wang, Y., & Du, C., et al. (2023). Bp neural network for non-invasive igbt junction temperature online detection. Microelectronics Reliability, 141, 114882-. Search in Google Scholar

[15] Rajesh, S., Shivangi, T., Rohit, V., & Manjari, T. (2024). Translation and adaptation of cognistat in hindi language: for computerized evaluation of cognitive functioning. Archives of Clinical Neuropsychology. Search in Google Scholar

[16] Yu, H., & Su, T. (2019). Semi-supervised cop-kmeans clustering analysis of language culture in english translation. Basic & clinical pharmacology & toxicology.(S9), 125. Search in Google Scholar

[17] Raisanen, T. (2020). The use of multimodal resources by technical managers and their peers in meetings using english as the business lingua franca. IEEE Transactions on Professional Communication, 63(2), 172–187. Search in Google Scholar

[18] Kim, H., & Chang, S. (2019). Effectiveness of role-play on discussion efficacy in translation education. Asia Life Sciences(3), 1325–1334. Search in Google Scholar