Research Article
Research on the Identification System of Power Big Data Attribute Entities based on Artificial Intelligence Algorithm
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342614, author={Jiangtao Guo and Tianfu Ma and Maihebubai Xiaokaiti and Rui Yin and Lulu Liu}, title={Research on the Identification System of Power Big Data Attribute Entities based on Artificial Intelligence Algorithm}, proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India}, publisher={EAI}, proceedings_a={ICSETPSD}, year={2024}, month={1}, keywords={identification system recurrent neural networks classifying attribute entities}, doi={10.4108/eai.17-11-2023.2342614} }- Jiangtao Guo
Tianfu Ma
Maihebubai Xiaokaiti
Rui Yin
Lulu Liu
Year: 2024
Research on the Identification System of Power Big Data Attribute Entities based on Artificial Intelligence Algorithm
ICSETPSD
EAI
DOI: 10.4108/eai.17-11-2023.2342614
Abstract
This paper conducts a comprehensive study on the identification system of power big data attribute entities using artificial intelligence algorithms. The purpose of the study is to construct an effective system that can accurately classify and analyze attribute entities in power big data. The methodology involves data preprocessing, feature extraction, and algorithm selection, with a specific focus on Recurrent Neural Networks (RNNs). The RNN architecture, including the computation of hidden states, is detailed in the paper. The experiment is conducted on a relevant dataset, with appropriate evaluation metrics to assess the system's performance. The results validate the effectiveness of the proposed identification system, showcasing its accuracy and efficiency in classifying attribute entities. The discussion highlights the system's strengths, limitations, and avenues for future research. Overall, this research contributes to the field of power big data analysis and provides valuable insights for practitioners and researchers alike.
