Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 196))

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Abstract

In English-Chinese machine translation, inaccurate feature semantic selection often leads to translation results not reaching the optimal solution. Therefore, the author proposes the design of an English-Chinese machine automatic translation system based on IoT feature extraction algorithm. IoT text is a text used to express IoT concepts, content, facts, data, etc. Its content intersects multiple fields and has characteristics such as cross-domain, professionalism, and standardization. Its discourse language style is rigorous and meticulous. Design the network architecture of the English-Chinese translation system using a three-layer architecture, construct a semantic map** model to extract the semantic features of the English-Chinese translation text, cluster the graph information of the features and determine the attributes, and achieve the feature extraction algorithm part of the English-Chinese machine automatic translation. Design the translation system software using embedded program scheduling and PLC bus technology, including the underlying database module, IoT control protocol module, cross-compilation module, and output interface module for translation conversion. Complete the integrated development of the English-Chinese machine automatic translation system through bus transmission automation control and low-level adaptation development. The comparative experimental results show that precise translation can be achieved through 500 iterations, which is much higher than other methods. The accuracy of the traditional Method 1 system and the traditional Method 2 system reached the highest of 94.4% and 94.7%, respectively, with a high number of iterations and excessive consumption of material resources. In practical applications, the number of iterations can be set to 200, achieving an accuracy rate of 98.4%, which can basically meet practical needs. It has been proven that the designed system can obtain the optimal translation solution and has a high translation accuracy.

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Chen, J. (2024). The Accuracy of English-Chinese Translation Based on the Internet of Things. In: Jansen, B.J., Zhou, Q., Ye, J. (eds) Proceedings of the 3rd International Conference on Cognitive Based Information Processing and Applications–Volume 1. CIPA 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 196. Springer, Singapore. https://doi.org/10.1007/978-981-97-1975-4_47

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