Advances in the Application of Network Analysis Methods in Traditional Chinese Medicine Research
D Tie, M He, W Li, Z Xiang - Phytomedicine, 2024 - Elsevier
Objective This review aims at evaluating the role and potential applications of network
analysis methods in the medicinal substances of traditional Chinese medicine (TCM) …
analysis methods in the medicinal substances of traditional Chinese medicine (TCM) …
Spatiotemporal polynomial graph neural network for anomaly detection of complex systems
M Ma, X Hua, Y Zhang, Z Zhai - Measurement, 2024 - Elsevier
Internet of Things systems are developed rapidly, there is a need for anomaly detection to
identify malicious data to guarantee that the systems perform under healthy condition …
identify malicious data to guarantee that the systems perform under healthy condition …
Graph Similarity Regularized Softmax for Semi-Supervised Node Classification
Y Yang, J Liu, W Wan - arXiv preprint arXiv:2409.13544, 2024 - arxiv.org
Graph Neural Networks (GNNs) are powerful deep learning models designed for graph-
structured data, demonstrating effectiveness across a wide range of applications. The …
structured data, demonstrating effectiveness across a wide range of applications. The …
[PDF][PDF] Neural network method for identifying potential defects in complex dynamic objects
The work is devoted to the development of a neural network method for identifying potential
defects in complex dynamic objects, such as, for example, helicopter turboshaft engines …
defects in complex dynamic objects, such as, for example, helicopter turboshaft engines …