Construction of artificial translation grading model based on BP neural network in college students’ translation grading system

Issue title: Special Section: Intelligent & fuzzy theory in engineering and science

Guest editors: Teresa Guarda, Isabel Lopes and Álvaro Rocha

Article type: Research Article

Authors: Yang, Ning^{; *}

Affiliations: Xi’an Fanyi University, Xi’an, China

Correspondence: [*] Corresponding author. Ning Yang, Xi’an Fanyi University, Xi’an, 710105, China. E-mail: ningyang3qu@sina.com.

Abstract: The construction of the artificial translation scoring model based on BP neural network has a positive effect on the improvement of college students’ translation performance. In order to promote the application of this kind of system in English teaching in our country, in this study, the author summarized the subjective topic scores in English teaching in our country, and then the author constructed the artificial translation scoring model of BP neural network. Compared with the example application, the comparison results show that the artificial translation scoring system based on BP neural network is more effective than the traditional scoring method. This study aims to provide reference for the continuous improvement and development of our English language teaching model.

Keywords: Translation, scoring system, BP neural network, artificial translation scoring model

DOI: 10.3233/JIFS-179188

Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6055-6062, 2019