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)

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)

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

Subjects:

Process of facial feature extraction and recognition method based on ipca algorithm. by Lu Lin (201289)

“…<p>Process of facial feature extraction and recognition method based on ipca algorithm.</p>…”

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. …”

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 CCCP algorithm of EQSVR based on ClipDCD. by Aiman Tahir (21485064)

Algorithm framework. by Zongjin Li (38031)

Subjects:

Comparison of hidden state prediction based on the Viterbi algorithm. by Heng Yang (590400)

The true value of the hidden state based on Viterbi algorithm. by Heng Yang (590400)

The predicted value of the hidden state based on Viterbi algorithm. by Heng Yang (590400)

Decision tree algorithms. by Mahbub E. Sobhani (22278967)

“…We have used Random Forest, Bagging, and Boosting (AdaBoost) algorithms and have compared their performances. We have used decision tree (C4.5) as the base classifier of Random Forest and AdaBoost classifiers and naïve Bayes classifier as the base classifier of the Bagging model. …”

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

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

Subjects:

Experimental data of ZFD-Net algorithm for defects. by Yang Gao (18005)

Effect images of CLAHE algorithm. by Yang Gao (18005)

Architecture of AGAN algorithm model. by Xing Chen (140292)

“…To address the issue of discrete missing data in cardiac disease, this paper proposes the AGAN (Attribute Generative Adversarial Nets) architecture for missing data filling, based on generative adversarial networks. This algorithm takes advantage of the strong learning ability of generative adversarial networks. …”

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”