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

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. …”

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)

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

MEA-BP neural network algorithm flowchart. by Dongling Ma (1269888)

Subjects:

Model’s measure methods. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

The block diagram of the ASO algorithm implementation for inverse modeling. by Ahmad Al-Talabi (21387479)

NAR dynamic neural network model. by Zhanni Huang (20577481)

“…Therefore, this article uses the random forest model and XGBoost algorithm to identify core price indicators, and uses an innovative rolling NAR dynamic neural network model to simulate and predict second-hand sailboat price data. …”

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Phenotype frequencies for each mutant and for complementation testing. by McKenna Feltes (11242085)

Backpropagation neural network structure. 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. …”

Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks by Zhihuang Yang (22530437)

“…By leveraging group <math><mrow><msub><mrow><mi>l</mi></mrow><mn>0</mn></msub></mrow></math>-norm constrained neural networks, the proposed approach aims to simultaneously extract crucial features and estimate the underlying model function with statistically guaranteed accuracy. …”

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

Phenotype frequency and complementation for additional novel DY alleles. by McKenna Feltes (11242085)

Licking behaviors and neural firings of the model. by Huu Hoang (9188747)

Subjects: “…supervised learning algorithms…”

The diagram of the LSTM neural network. by Mohd Sakib (20565228)

Neural Network Structure Parameters. by Yu Jie Guang (22184340)

Subjects:

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. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”

Flowchart of GA-PSO-BP neural network model. by Jining Wang (3369305)

“…To address this issue, the research employs a genetic-particle swarm optimization (GA-PSO) algorithm and develops a GA-PSO-BP neural network model through the integration of the BP neural network. …”