Block model and waste dump parameters. by Jingsi Lin (22386427)

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Comparison of algorithms across metrics in test problems. by Jihui Hu (19812736)

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Main code. by Jingguo Bi (21439766)

Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. by Martina Bukač (20161460)

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Material flows produced by the proposed SA-based algorithm. by Jingsi Lin (22386427)

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Performance evaluation of the proposed algorithm compared to the exact method. by Jingsi Lin (22386427)

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ANOVA was performed to test the differences between the algorithms for each indicator. by Jihui Hu (19812736)

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Production plan produced by the SA-based algorithm for Case A. by Jingsi Lin (22386427)

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ROC curves of four models for wasting. by Md. Merajul Islam (12646837)

“…</p><p>Results</p><p>The XGB-based model outperformed the other models, with the accuracy and AUC respectively 81.73% and 0.802 for stunting, 76.15% and 0.622 for wasting, and 79.13% and 0.712 for underweight. …”

The selection process of the ONDL model among other models. by Nour Eldeen Mahmoud Khalifa (19259450)

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<b>Robot_gripper_design</b> by Ma Haohao (19780875)

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Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. by Jiren CAO (20442214)

Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”

Chromosome coding. by Junjie He (700642)

Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS) by bowen pang (21837359)

“…<p dir="ltr">The open-source content is the source code of a land use spatial optimization model (SSFLA-MLAS) that couples the spatial leapfrog algorithm with multi-level multi-agent systems. …”

SHAP summary plot of the XGB model for wasting. by Md. Merajul Islam (12646837)

“…</p><p>Results</p><p>The XGB-based model outperformed the other models, with the accuracy and AUC respectively 81.73% and 0.802 for stunting, 76.15% and 0.622 for wasting, and 79.13% and 0.712 for underweight. …”

Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

Comparison of different algorithms. by Jiandong Qiu (20389944)

The ranking of algorithms with MPTM mutation by TOPSIS. by Jalal- ud-Din (21474307)

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