بدائل البحث:
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
tasks based » task based (توسيع البحث), cases based (توسيع البحث)
data based » data used (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
tasks based » task based (توسيع البحث), cases based (توسيع البحث)
data based » data used (توسيع البحث)
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161
primary mouse RT single cell RNA-seq
منشور في 2023"…The clustering was conducted using the graph-based modularity optimization Louvain algorithm implemented in Seurat v3. …"
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162
Results of Comprehensive weighting.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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163
The prediction error of each model.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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164
VIF analysis results for hazard-causing factors.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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165
Benchmark function information.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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166
Geographical distribution of the study area.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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167
Results for model hyperparameter values.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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168
Flow chart of this study.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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169
Stability analysis of each model.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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170
Robustness Analysis of each model.
منشور في 2025"…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …"
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171
Proposed method approach.
منشور في 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. …"
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172
LSTM model performance.
منشور في 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. …"
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173
Descriptive statistics.
منشور في 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. …"
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174
CNN-LSTM Model performance.
منشور في 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. …"
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175
MLP Model performance.
منشور في 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. …"
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176
RNN Model performance.
منشور في 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. …"
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177
CNN Model performance.
منشور في 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. …"
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178
Bi-directional LSTM Model performance.
منشور في 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. …"
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179
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180