Ensemble learning and deep learning-based defect detection in power generation plants
One of the key factors driving a country’s economic development and ensuring the sustainability of its industries is the constant availability of electricity. This is normally provided by the national grid. However, the power supply is not always stable in developing countries where new businesses,...
Saved in:
| Main Authors: | Atemkeng Marcellin, Osanyindoro Victor, Rockefeller Rockefeller, Hamlomo Sisipho, Mulongo Jecinta, Ansah-Narh Theophilus, Tchakounté Franklin, Fadja Arnaud Nguembang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2024-11-01
|
| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2023-0283 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EGMA: Ensemble Learning-Based Hybrid Model Approach for Spam Detection
by: Yusuf Bilgen, et al.
Published: (2024-10-01) -
CRASA: Chili Pepper Disease Diagnosis via Image Reconstruction Using Background Removal and Generative Adversarial Serial Autoencoder
by: Jongwook Si, et al.
Published: (2024-10-01) -
Water Quality Inversion Framework for Taihu Lake Based on Multilayer Denoising Autoencoder and Ensemble Learning
by: Zhihao Sun, et al.
Published: (2024-12-01) -
Func-Bagging: An Ensemble Learning Strategy for Improving the Performance of Heterogeneous Anomaly Detection Models
by: Ruinan Qiu, et al.
Published: (2025-01-01) -
Advancing Algorithmic Adaptability in Hyperspectral Anomaly Detection with Stacking-Based Ensemble Learning
by: Bradley J. Wheeler, et al.
Published: (2024-10-01)