Optimization process of BO algorithm. حسب Hoa Thi Trinh (20347834)

"…The results show that Gaussian Process emerged as the most efficient solution compared to other optimization algorithms, providing the lowest Mean Square Error and achieving a prediction R² of 0.998 for the training set, 0.972 for the validation set and 0.984 for the test set, while BO—Random Forest and Random Search performed as well on the training and test sets as Gaussian Process but significantly worse on the validation set, specifically R² on the validation set of BO—Random Forest and Random Search were 0.970 and 0.969 respectively over the entire dataset including all cross-sectional shapes of the RC wall. …"

A framework for improving localisation prediction algorithms. حسب Sven B. Gould (12237287)

Boxplots of the best subject-dependent correlations in the intensity prediction. حسب Isabel Barradas (20614853)

Performance of algorithms outside the training species. حسب Sven B. Gould (12237287)

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. حسب Burak Alakent (463512)

CY45-0.5/1#9 Code file for data processing and prediction results. حسب Yanhua Xian (21417128)

Algorithm process. حسب Wei Cui (92129)

Visualization process of AOSD algorithm. حسب Lu Liu (171341)

Processing pipeline dependency chain. حسب Michael E. Kim (21956727)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

An improved Grey Wolf Optimization based heuristic initialization algorithm for feature selection in P2P lending default prediction حسب Muhammad Sam'an (20649621)

"…<p>This research addressed the problem of irrelevant feature and high-dimensional data in Peer-to-Peer (P2P) lending, which made the process hard to predict default accurately. …"

Data and code resources. حسب Sam Hall-McMaster (10343795)

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

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

The interleaved processes. حسب Dawei Wang (471687)

The process of IHWGWO. حسب Dawei Wang (471687)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

GA pseudo-code. حسب Jianpeng Zhang (528185)

"…The introduction of gated recurrent unit addresses the dependency of time series data and effectively solves the problem of gradient vanishing or exploding in traditional recurrent neural networks when processing long sequence data. …"

Overall process planning. حسب Dawei Wang (471687)

CatBoost algorithm structure to predict clinical outcome. حسب Andrew McDonald (2307400)

الموضوعات: "…provide interpretable predictions…"

Workflow of our study to evaluate the performance of GNNs compared to benchmark algorithms. حسب Daniel Walke (21680915)