التفاصيل البيبلوغرافية
| العنوان: |
Application of Improved BPNN Algorithm in GIS Insulation Defect Type Identification |
| المؤلفون: |
Feng, X Y, Hu, X L, Yong, J, Yang, B, Sun, X B, Duan, Y B, Meng, H L, Xu, Y P |
| المصدر: |
Journal of Physics: Conference Series ; volume 1346, issue 1, page 012035 ; ISSN 1742-6588 1742-6596 |
| بيانات النشر: |
IOP Publishing |
| سنة النشر: |
2019 |
| الوصف: |
In this paper, a new BP neural network has been built with GA algorithm, which possesses high effectivity, parallel processing ability and global search feature, in order to overcome the original shortcomings such as the low convergence rate and the confusion of local minimum points. Ten parameters of partial discharge characteristics are obtained as input of BPNN to identify four typical insulation defect physical models designed in this paper for the purpose of measuring the recognition accuracy of the improved BPNN. Experiments show that the improved BPNN has a better performance of convergence speed and recognition accuracy than that of adaptive momentum BP neural network. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| DOI: |
10.1088/1742-6596/1346/1/012035 |
| DOI: |
10.1088/1742-6596/1346/1/012035/pdf |
| الإتاحة: |
https://doi.org/10.1088/1742-6596/1346/1/012035Test |
| حقوق: |
http://creativecommons.org/licenses/by/3.0Test/ ; https://iopscience.iop.org/info/page/text-and-data-miningTest |
| رقم الانضمام: |
edsbas.DE1F980A |
| قاعدة البيانات: |
BASE |
