Performance of machine learning algorithms. by Wenxue Liu (6877754)

List of the time used by each algorithm. by JiaMing Gong (20427837)

“…In this manner high quality and common samples are randomly selected for training the classifier. Finally, to solve the issue of concept drift, EDAC designs and implements an ensemble classifier that uses a self-feedback strategy to determine the initial weight of the classifier by adjusting the weight of the sub-classifier according to the performance on the arrived data chunks. …”

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

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

PLS-SEM algorithm. by Ernest Nyamekye (18451455)

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Overview of the C&CG method. by Tianhe Sun (21145341)

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Data embedding by using Neural Quantum Embedding (NQE). by Aninda Astuti (21736334)

Comparison of planning results for different uncertainty quantification methods. by Tianhe Sun (21145341)

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Results on solving TSS using different evolutionary and greedy algorithms. by Alexander Andreev (16822333)

“…<p>Results on solving TSS using different evolutionary and greedy algorithms.…”

Solving flow chart of the IBBPSO algorithm. by Kuiyuan Pan (21145338)

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Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

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Metaheuristic algorithms for solving DNA-related problems. by Eslam Hamouda (5172083)

Proposed Algorithm. by Hend Bayoumi (22693738)

“…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”

Convergence curves for all algorithms. by Genliang Li (5816264)

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Parameter Settings for competitive algorithms. by Genliang Li (5816264)

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An instance of the IPP that can be solved by applying the algorithms for the DPP. by Jordan Moutet (21800145)

Classification performance results using 5-fold cross-validation for the training datasets after applying the data imbalance tool, SMOTE and NQE for data embedding. The values with... by Aninda Astuti (21736334)

Classification performance results using 5-fold cross-validation for the training datasets after applying the data imbalance tool, SMOTE and NQE for data embedding. The values with... by Aninda Astuti (21736334)

Details of multiple GWO algorithm variants. by Genliang Li (5816264)

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