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

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

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The schematic diagram of benefit-form binary utility measure functions and. حسب Chao Yu (562804)

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. حسب Tehnan I. A. Mohamed (16846175)

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

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

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

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

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

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

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

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

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

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

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

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Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF حسب Haidi Wang (9694004)

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…"

Bayesian sequential design for sensitivity experiments with hybrid responses حسب Yuxia Liu (1779592)

"…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …"