I-NSGA-II-RF algorithm. by Xiaohua Zeng (793632)

“…Finally, the selected feature subset and parameters are input to the RF for training, prediction, and iterative optimization. Experimental results show that the I-NSGA-II-RF algorithm has the highest average accuracy, the smallest optimal solution set, and the shortest running time compared to the unmodified multi-objective feature selection algorithm and the single target feature selection algorithm. …”

The pareto front obtained by each algorithm. by Xiaohua Zeng (793632)

“…Finally, the selected feature subset and parameters are input to the RF for training, prediction, and iterative optimization. Experimental results show that the I-NSGA-II-RF algorithm has the highest average accuracy, the smallest optimal solution set, and the shortest running time compared to the unmodified multi-objective feature selection algorithm and the single target feature selection algorithm. …”

Comparison of multi-algorithm convergence curves. by Chengcheng Ding (9013862)

“…To address this, a coordinated framework is proposed, integrating a dynamic carbon emission trading (CET) mechanism with green certificate trading (GCT) and a Multi-Strategy Ameliorated Goose Optimization (MSAGOOSE) algorithm. …”

Hyperparameters of various algorithms. by Chengcheng Ding (9013862)

“…To address this, a coordinated framework is proposed, integrating a dynamic carbon emission trading (CET) mechanism with green certificate trading (GCT) and a Multi-Strategy Ameliorated Goose Optimization (MSAGOOSE) algorithm. …”

Parameter settings of all metaheuristic algorithms for optimizing RVFL. by Emad T. Elkabbash (11731506)

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Private parameter settings of each metaheuristic optimization algorithm. by Emad T. Elkabbash (11731506)

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Multi-objective optimization results and the corresponding optimal trajectory. by Jian Kang (118630)

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The algorithm of screening extended regions in targeted sequencing. by Xuwen Wang (527554)

An illustration of the 2-dimensional target space decomposition. by Luda Zhao (10947655)

Algorithm of M3VR. by Qi Xing (5844119)

An Efficient Algorithm for Minimizing Multi Non-Smooth Component Functions by Minh Pham (2458399)

Membership function of each target. by Tianrui Zhang (2294542)

Algorithm metrics results and engineering application data in the paper : Energy-Efficient Many-objective Flexible Flow-shop Scheduling Optimization Based on Positive Projection Gr... by Zheng Zhang (12023600)

A probabilistic framework based on the gradient descent algorithm for multi-objective land use optimization by Haowen Luo (13873976)

“…<p dir="ltr">This is an implementation of the probabilistic framework with the probabilistic multi-objective optimization of land use (pMOLU) model and gradient descent algorithm for land use optimization.…”

Fast Matrix-Free Methods for Model-Based Personalized Synthetic MR Imaging by Subrata Pal (2513494)

Time in minutes for each algorithm’s execution time. by Emad T. Elkabbash (11731506)

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Algorithm flowchart of OFEO. by Wenshun Sheng (21485393)

“…<div><p>A real-time stable multi-target tracking method based on the enhanced You Only Look Once-v8 (YOLOv8) and the optimized Simple Online and Realtime Tracking with a Deep association metric (DeepSORT) for real-time stable multi-target tracking (S-YOFEO) is proposed to address the issue of target ID transformation and loss caused by the increase of practical background complexity. …”

Optimized training data organization (a white node represents a channel facies value, a black node represents a background value, and a shaded node represents a null value). by Jianpeng Yao (11008872)

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Execution time of RVFL+ JS against other metaheuristic algorithms. by Emad T. Elkabbash (11731506)

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Measurement FPR of RVFL+ JS against other metaheuristic algorithms. by Emad T. Elkabbash (11731506)

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