A Mean Weighted Squared Error-based Neural Classifier for Intelligent Pattern Recognition in Smart Grids
Supervised learning is widely used in pattern recognition and classification due to its strong ability to enhance data accuracy. Loss functions have proven to be a critical factor in enhancing the predictive accuracy of intelligent classifiers with diverse architectures and characteristics. This pap...
Saved in:
| Main Authors: | Mehdi Khashei, Mehrnaz Ahmadi, Fatemeh Chahkoutahi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525005204 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research of Online Error Prediction and Parallel Algorithm for Voltage Transformer in Smart Grid
by: Xin Xianfeng, et al.
Published: (2024-12-01) -
Hardware-Based Calculation of Mean Square Error for Automatic Target Recognition in SAR Images
by: Lucas Urbanski, et al.
Published: (2025-01-01) -
PV Generation Prediction Using Multilayer Perceptron and Data Clustering for Energy Management Support
by: Fachrizal Aksan, et al.
Published: (2025-03-01) -
Mean Squared Error Representative Points of Pareto Distributions and Their Estimation
by: Xinyang Li, et al.
Published: (2025-02-01) -
Performance analysis of global local mean square error criterion of stochastic linearization for nonlinear oscillator
by: Luu Xuan Hung, et al.
Published: (2019-03-01)