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

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Example of back-translation based on Jacob and Shushma [8]. by Rodrigo Gutiérrez Benítez (19746443)

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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. …”

Data and Scripts for 'A Predictive Model for Attention-deficit/hyperactivity Disorder and Its Subtypes in Children: A Back-propagation Neural Network Optimized with Genetic Algorithms Based on Multidimensional Cognitive Ability Tests' by Wang (20310746)

“…However, previous artificial intelligence-based diagnostic models for attention-deficit/hyperactivity disorder have faced challenges in achieving a balance among cost-effectiveness, low operational threshold, and high predictive accuracy. …”

Comparison of results based on CycleGAN method. by Xiaojun Wang (50332)

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Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. by Tomokaze Shiratori (9635271)

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Augmentation levels with back-translation. by Rodrigo Gutiérrez Benítez (19746443)

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Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. …”

Data and Scripts for 'Application of Multidimensional Cognitive Ability Tests in Computer-Assisted Diagnosis of Attention-Deficit/Hyperactivity Disorder and Its Subtypes in Children: Based on A Genetic Algorithm Optimized Back-Propagation Neural Network Predictive Model' by Wang (20310746)

“…However, previous artificial intelligence-based diagnostic models for attention-deficit/hyperactivity disorder have faced challenges in achieving a balance among cost-effectiveness, low operational threshold, and high predictive accuracy. …”

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Minimal data set. by Peiwen Zhang (1863202)

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Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”

Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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