Search alternatives:
process optimization » model optimization (Expand Search)
models optimization » model optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
primary data » primary care (Expand Search)
a process » _ process (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
process optimization » model optimization (Expand Search)
models optimization » model optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
primary data » primary care (Expand Search)
a process » _ process (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
-
141
Proposed model tuned hyperparameters.
Published 2024“…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …”
-
142
Proposed model sensitivity outcome.
Published 2024“…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …”
-
143
CNN-LSTM Model performance.
Published 2024“…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …”
-
144
-
145
-
146
-
147
Proposed model specificity and DSC outcomes.
Published 2024“…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …”
-
148
Bi-directional LSTM Model performance.
Published 2024“…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …”
-
149
Prediction results of different models.
Published 2024“…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”
-
150
Event-driven data flow processing.
Published 2025“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
-
151
-
152
S1 Data -
Published 2025“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”
-
153
-
154
-
155
-
156
-
157
-
158
-
159
-
160