Search alternatives:
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
primary data » primary care (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
guided optimization » based optimization (Expand Search), model optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
primary data » primary care (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
-
1
Performance on GradEva.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
-
2
The considered test problems.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
-
3
Performance on FunEva.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
-
4
Performance on Iter.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
-
5
Continuation of Table 2.
Published 2024“…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
-
6
Models’ performance without optimization.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
7
Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf
Published 2023“…Objective<p>Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. …”
-
8
RNN performance comparison with/out optimization.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
9
-
10
-
11
Datasets used for the study and their sources.
Published 2023“…Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. …”
-
12
-
13
-
14
Proposed method approach.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
15
LSTM model performance.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
16
Descriptive statistics.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
17
CNN-LSTM Model performance.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
18
MLP Model performance.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
19
RNN Model performance.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
20
CNN Model performance.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”