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

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

Pareto optimal front result of MOCOA. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Confusion matrix. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 1. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Performance validation on the MIT-BIH database. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Performance comparison with other papers. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 2. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 0. by Hang Zhao (143592)

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

The flowchart of GWO-VMD method. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Partial polishing of experimental data. by Ma Haohao (22177538)

Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4 by Berith Atemoztli De la Cruz Sánchez (21758708)

“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. …”

Polishing experimental data (<i>μ<i>m</i></i>). by Ma Haohao (22177538)

Ricker seismic profile. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Noise reduction on testing sets from STEAD. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

SNR comparison of real-field seismic profile. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

The 147th single trace. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Confusion_Matrix_Data.zip by Mohammad Farhad Bulbul (21003494)

Machine Learning-Assisted Accelerated Research of Energy Storage Properties of BaTiO₃–BiMeO₃ Ceramics by Jian Liu (33711)

“…Three distinct feature vector spaces were constructed based on the physicochemical characteristics of constituent elements, related property information, and sintering process parameters. …”