التفاصيل البيبلوغرافية
| العنوان: |
Improved Cluster Intelligent and Complex Optimization Algorithm for Power Equipment CAD-Assisted Intelligent Operation and Maintenance. |
| المؤلفون: |
Song, Yinguan, Zou, Yu, Su, Yifeng, Wang, Ming, Xie, Zhenjun, Chen, Henglong, Sang, Zhongqing |
| المصدر: |
Advances in Multimedia; 3/21/2022, p1-11, 11p |
| مصطلحات موضوعية: |
MATHEMATICAL optimization, DATA quality, ELECTRONIC data processing |
| مستخلص: |
By using the data collected by the cluster intelligent and complex optimization of the power system equipment, the cluster intelligent and complex optimization algorithms are introduced into the CAD-aided intelligent operation and maintenance of power system equipment (CAD-IOMPSE). Based on this, the CAD-aided intelligent operation and maintenance graph of power system equipment is used to apply the cluster intelligent complex data contained in the quality inspection of the different types of data obtained to restrict the relationship between different entities for the value of knowledge contained in the collected power data in the operation process and control stage of the power system. According to the types of equipment with problems in the operation of power system, the defects and problems are quickly diagnosed to quickly locate the problems and give solutions. Finally, the results of example analysis show that compared with the traditional naming entity recognition algorithm, BiLSTM-softmax and Seq2Seq-Attention model, the algorithm in this study is better than the traditional algorithm in the three evaluation index values of accuracy, recall, and F1 value. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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