2 citations · 2 across the 5 of their papers we have counts for
5 papers
Feature Selection Based on Orthogonal Constraints and Polygon Area
Zhenxing Zhang, Jun Ge, Zheng Wei +2
The goal of feature selection is to choose the optimal subset of features for a recognition task by evaluating the importance of each feature, thereby achieving effective dimension…
Cross-tokamak Disruption Prediction based on Physics-Guided Feature Extraction and domain adaptation
Chengshuo Shen, Wei Zheng, Bihao Guo +11
The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in dis…
Is It the End? Guidelines for Cinematic Endings in Data Videos
Xian Xu, Aoyu Wu, Leni Yang +4
Data videos are becoming increasingly popular in society and academia. Yet little is known about how to create endings that strengthen a lasting impression and persuasion. To fulfi…
Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor
Wei Zheng, Fengming Xue, Ming Zhang +12
Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption disc…
Fast Graph Subset Selection Based on G-optimal Design
Zhengpin Li, Zheng Wei, Jian Wang +2
Graph sampling theory extends the traditional sampling theory to graphs with topological structures. As a key part of the graph sampling theory, subset selection chooses nodes on g…