GBO framework used to estimate the battery SOH. by Mouncef El Marghichi (17328361)

The convergence curve of each optimization algorithm under the test function. by Hao Yang (328526)

Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art CEA-ES algorithms using CEC2014 functions. by Yang Cao (53545)

Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100. by Yang Cao (53545)

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Total primary energy demand by fuel in China. by Da Lian (18880882)

Iteration curve of the optimization process. by Meijun Shang (22806461)

Average ranks for all algorithms across all problems and all dimensions using CEC2014. by Yang Cao (53545)

Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art DE variants using CEC2014 functions. by Yang Cao (53545)

Average ranks for all algorithms across all problems for D = 30, 50, and 100 using CEC2014. by Yang Cao (53545)

Datasets of computational processes. by Yixuan Lu (9987980)

Subjects:

Flow chart of the Improved Kepler Orbital Algorithm (IKOA). by Hao Yang (328526)

Algorithms and evaluation metrics integrated in the COPS framework. by Teemu J. Rintala (19333003)

Overview of the cohort definition process. by Nicola Lazzarini (3528197)

Robustness Analysis of each model. by Hao Yang (328526)

“…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. …”

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects: