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)

Modeling approach and network generating algorithm. by Matthew Aguirre (9558032)

“…<p><b>(A)</b> Overview of network generating algorithm, based on a growth process with preferential attachment. …”

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)

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. …”

Greedy optimization algorithm. by Alexis Bénichou (19832361)

Obtained heat map for regression-based algorithms. by Akshansh Mishra (21001499)

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Fault diagnosis model based on Kepler algorithm and attention mechanism. by Yu Jie Guang (22184340)

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Algorithm performance comparison. by Haiyan Wang (25821)

Evaluation of model aggregation algorithms. by JiaMing Wang (334865)

“…Finally, the paper designs a deep learning model based on two-dimensional convolutional neural networks and bidirectional gated recurrent units (2DCNN-BIGRU) to handle incomplete data features and missing labels in network traffic data. …”

Feature importance plot obtained for regression-based algorithms. by Akshansh Mishra (21001499)

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Comparison of different optimization algorithms. by Hang Zhao (143592)

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Improve algorithm settings. by Hui Zhao (7395)

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Algorithm framework. by Zongjin Li (38031)

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Flowchart of algorithm principles. by Wenjuan Zhou (115285)

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Search algorithm performance comparison. by Zhaohui Du (414105)

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.…”

Fitness versus iterations based on different clustering algorithms. by Yiwei Zhao (2729758)

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Algorithm flow based on CL-EPIDTN. by Fang Yang (123514)

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. …”