Assessment of the accuracy of Chinese and English transfer of circulating energy storage equipment
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Rui Wang
Abstract
With the advancement of globalization, the rapid development of circulating energy has attracted the attention of all walks of life. Timely monitoring of the accuracy assessment in the Chinese and English transfer environment has an extremely important impact on understanding and promoting the development of circulating energy storage equipment. In the process of Chinese and English transfer, the circulation of energy storage equipment has become more convenient and quickly accepted by users because of its wide application. Based on this background, this study proposed an ICE-LDA model based on the LDA model for developing accuracy assessment in Chinese and English transfer. Through the method of transfer assessment in Chinese and English, the detection of transfer information in Chinese and English and the similarity of accuracy distribution are measured. This study will model the transfer data collected in Chinese and English. In this process, this study will use the TF-IDF algorithm to extract the transfer information in circulating energy storage devices to improve the accuracy of Chinese and English.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.
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Conflict of interest: The author states no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
References
1. Dmitrievna, BD, Valerievich, DD, Sergeyevich, AV, Stanislavovich, PM, Konstantinovich, KD, Dmitrievich, VA, et al.. Many heads but one brain: fusion Brain-a single multimodal multitask architecture and a competition br. Comput Opt 2023;47:185–95. https://doi.org/10.18287/2412-6179-co-1220.Search in Google Scholar
2. Chang, Y. Constructing a demand-driven college English learning environment in higher education institutions. Appl Artif Intell. 2023;37. https://doi.org/10.1080/08839514.2023.2211459.Search in Google Scholar
3. Chen, ZR, Li, IS, Zhang, HX, Preum, S, Stankovic, JA, Ma, MY. CitySpec with shield: a secure intelligent assistant for requirement formalization. Pervasive Mob Comput 2023;92. https://doi.org/10.1016/j.pmcj.2023.101802.Search in Google Scholar
4. Zhipeng, G, Haishan, G, Liming, L, Pengfei, S, Siyao, L, Yunfeng, Z, et al.. Nonlinear finite element analysis of post-tensioned precast prestressed slab-beam-column joints. Structures 2023;58. https://doi.org/10.1016/j.istruc.2023.105438.Search in Google Scholar
5. Harikumar, N, Surendar, RS. Balanced performance merit on wind and solar energy contact with clean environment enrichment. IEEE J Electron Devices Soc. 2024:1.Search in Google Scholar
6. Kumar, PM, Kamruzzaman, MM, Alfurhood, BS, Hossain, B, Nagarajan, H, Sitaraman, SR. Balanced performance merit on wind and solar energy contact with clean environment enrichment. IEEE J Electron Devices Soc 2024;12:808–23. https://doi.org/10.1109/jeds.2024.3358087.Search in Google Scholar
7. Dharma, TV. Optimizing cloud computing environments for big data processing. Int J Eng Sci Res 2023;13. ISSN 2277-2685.Search in Google Scholar
8. Narla, S, Peddi, S, Valivarthi, DT, Kethu, SS, Natarajan, DR, Kurniadi, D. FOG computing based energy efficient and secured iot data sharing using SGSOA and GMCC. Sustain Comput: Inform Syst 2025;46:101109. https://doi.org/10.1016/j.suscom.2025.101109.Search in Google Scholar
9. Lane, G, Vatanparast, H. Immigrant families? Experience of the Canadian food and nutrition environment. Appl Physiol Nutr Metabol 2023;48:445–54. https://doi.org/10.1139/apnm-2022-0346.Search in Google Scholar PubMed
10. Jayaprakasam, BS, Hemnath, R. Optimized microgrid energy management with cloud-based data analytics and predictive modelling. Int J Mod Electron Commun Eng 2018;6:79–87.Search in Google Scholar
11. Ortiz-Zambrano, JA, Espin-Riofrio, C, Montejo-Ráez, A. Combining transformer embeddings with linguistic features for complex word identification. Electronics 2023;12. https://doi.org/10.3390/electronics12010120.Search in Google Scholar
12. Rathcke, T, Lin, CY. An acoustic study of rhythmic synchronisation with natural English speech. J Phonetics 2023;100. https://doi.org/10.1016/j.wocn.2023.101263.Search in Google Scholar
13. Rocci, A. On the gravitational effects of light. Eur Phys J H 2023;48. https://doi.org/10.1140/epjh/s13129-023-00055-2.Search in Google Scholar
14. Subramanian, R, Aruchamy, P. An effective speech emotion recognition model for multi-regional languages using threshold-based feature selection algorithm. Circ Syst Signal Process 2023;43:114–21.10.1007/s00034-023-02571-4Search in Google Scholar
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