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resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
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Showing 1 - 20 results of 23 for search '(( binary water resource optimization algorithm ) OR ( pine tree process optimization algorithm ))', query time: 0.54s Refine Results
  1. 1
    Hyperparameter settings for the optimization algorithms.

    Hyperparameter settings for the optimization algorithms. by Ahmed M. Elshewey (21463867)

    Published 2025
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  2. 2
    Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms.

    Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms. by Ahmed M. Elshewey (21463867)

    Published 2025
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  3. 3
    Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm.

    Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

    Published 2025
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  4. 4
    Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.

    Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

    Published 2025
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  5. 5
    The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms.

    The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

    Published 2025
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  6. 6
    Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.

    Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

    Published 2025
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  7. 7
    Adaptive dynamic algorithm for Australia rainfall.

    Adaptive dynamic algorithm for Australia rainfall. by Ahmed M. Elshewey (21463867)

    Published 2025
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  8. 8
    The outcomes of the ANOVA results for the proposed AD-PSO-Guided WOA-LSTM algorithm for rainfall prediction.

    The outcomes of the ANOVA results for the proposed AD-PSO-Guided WOA-LSTM algorithm for rainfall prediction. by Ahmed M. Elshewey (21463867)

    Published 2025
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  9. 9
    Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm.

    Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm. by Ahmed M. Elshewey (21463867)

    Published 2025
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  10. 10
    Metrics for evaluating the performance of the proposed model.

    Metrics for evaluating the performance of the proposed model. by Ahmed M. Elshewey (21463867)

    Published 2025
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  11. 11
    The AD-PSO-Guided WOA LSTM framework.

    The AD-PSO-Guided WOA LSTM framework. by Ahmed M. Elshewey (21463867)

    Published 2025
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  12. 12
    Hyperparameters of the LSTM Model.

    Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

    Published 2025
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  13. 13
    Prediction results of individual models.

    Prediction results of individual models. by Ahmed M. Elshewey (21463867)

    Published 2025
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  14. 14
    NZGRC 2022 Poster: Assessing Optimal Flight and Capture Parameters for Post-Thinning Quality Control in Radiata Pine Forest Stands using Unmanned Aerial Vehicles

    NZGRC 2022 Poster: Assessing Optimal Flight and Capture Parameters for Post-Thinning Quality Control in Radiata Pine Forest Stands using Unmanned Aerial Vehicles by Atman Dhruva (13442901)

    Published 2022
    “…These results are expected to inform us of the optimal photogrammetry parameters required for data capture in thinned stands of radiata pine. …”
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  15. 15
    Classification performance after optimization.

    Classification performance after optimization. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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  16. 16
    ANOVA test for optimization results.

    ANOVA test for optimization results. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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  17. 17
    Wilcoxon test results for optimization.

    Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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  18. 18
    Wilcoxon test results for feature selection.

    Wilcoxon test results for feature selection. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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  19. 19
    Feature selection metrics and their definitions.

    Feature selection metrics and their definitions. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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  20. 20
    Statistical summary of all models.

    Statistical summary of all models. by Amal H. Alharbi (21755906)

    Published 2025
    “…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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