A Machine Intelligence Evaluation System Based on Internet Automation Technology and Deep Learning

Abstract

To realize the machine intelligence evaluation system, a method based on Internet automation technology is proposed. Firstly, then extracted and optimized, and finally combined with each other. A BP neural machine evaluation system is designed to compare the results of machine evaluation with the average value of teachers’ independent evaluation by selecting 20 students’ test paper translation samples from a class randomly. The test results show that by selecting a random class of 20 students, the comparison of machine evaluation results and teacher independent evaluation shows that the error range of the evaluation results of 20 samples is-5.6% -6.7%, which is within the allowable range of translation evaluation and meets the requirements of teaching evaluation. It is proved that the Chinese-English machine translation evaluation system based on Internet automation technology has excellent performance, which can improve the reliability and accuracy of the evaluation and reduce the degree of human intervention and misjudgment rate of the Chinese translation evaluation.