Search alternatives:
fastica algorithm » hastings algorithm (Expand Search), fusion algorithm (Expand Search), rast algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
cnn algorithm » mean algorithm (Expand Search), _ algorithm (Expand Search), ii algorithm (Expand Search)
implement » implemented (Expand Search), implementing (Expand Search)
fastica algorithm » hastings algorithm (Expand Search), fusion algorithm (Expand Search), rast algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
cnn algorithm » mean algorithm (Expand Search), _ algorithm (Expand Search), ii algorithm (Expand Search)
implement » implemented (Expand Search), implementing (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
-
7
-
8
Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"
Published 2024“…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…”
-
9
CNN model evaluation.
Published 2025“…The hybrid stacking approach did an excellent implementation using Decision Trees, Random Forest, and XGBoost as base learners with Gradient Boosting as a meta-learner, which managed to record an accuracy of 90%. …”
-
10
ROC curve CNN.
Published 2025“…The hybrid stacking approach did an excellent implementation using Decision Trees, Random Forest, and XGBoost as base learners with Gradient Boosting as a meta-learner, which managed to record an accuracy of 90%. …”
-
11
-
12
-
13
Confusion matrix evaluation of CNN.
Published 2025“…The hybrid stacking approach did an excellent implementation using Decision Trees, Random Forest, and XGBoost as base learners with Gradient Boosting as a meta-learner, which managed to record an accuracy of 90%. …”
-
14
-
15
-
16
-
17
-
18
CNN structure for feature extraction.
Published 2025“…By employing contrast-limited adaptive histogram equalization (CLAHE), contrast-enhanced images were generated with minimal noise and prominent distinctive features. Subsequently, a CNN-SVD-Ensemble model was implemented to extract important features and reduce dimensionality. …”
-
19
-
20