Special Session Ⅰ- Data Mining and Fault Diagnosis
Chair: Yuanjiang Li, Jiangsu University of Science and Technology, China
Co-chairs: Ruijie Zhao, Jiangsu University, China
Jin Zhu, Jiangsu University of Science and Technology, China
Co-organized by Jiangsu University of Science and Technology, China
Keywords:
Time series prediction
Time series anomaly detection
Fault diagnosis
Interpretable artificial intelligence
Summary:
Data mining is a creative process involving a large number of different technologies and knowledge, aimed at extracting knowledge of interest from data in large databases. This process requires predetermining the steps to be taken and the goals to be achieved to ensure the orderly implementation and success of data mining.
Fault diagnosis is a process of collecting and analyzing data aimed at determining the cause of a fault and how to prevent its recurrence. This process involves almost all industries and is an important means to ensure industrial safety and improve production efficiency.
In summary, data mining is a process of extracting useful information from large amounts of data, while fault diagnosis is a process of determining the cause of faults and taking corresponding measures by collecting and analyzing data. The two methods are interrelated in industrial applications, jointly promoting the improvement of industrial safety and efficiency.
Topics:
Univariate/Multivariate Time Series Prediction and Modeling Type Stability Analysis
Time Series Anomaly Detection - Anomalies in Point/Subsequences Frequently Analyze
Deep Learning Methods in Fault Diagnosis and Decision-making Assistance Application in the Field and its Interpretability Analysis
Knowledge Graph Method in the Field of Fault Diagnosis
Special Session Ⅱ- Network Learning and Propagation Dynamics Analysis (DDL: 2025.5.30)
Chair: Xuzhen Zhu, Beijing University of Posts and Telecommunications, China
Co-chairs: Yuexia Zhang, Beijing Information Science and Technology University, China
Yujie Yang, Henan Normal University, China
Zijia Huang, National Key Laboratory of Multi-domain Data Collaborative Processing and Control, China
Keywords:
Complex Network
Propagation Dynamics
Link Prediction
Recommendation Algorithm
Air-Ground Integrated Network
Artificial Intelligence
Summary:
The topic "Network Learning and Propagation Dynamics" will focus on the latest advancements in complex networks, propagation dynamics, link prediction, and recommendation algorithms. The structures of complex networks play a crucial role in various applications in modern society, including social media, Space-Air-Ground Integrated Network（SAGIN） communication network information dissemination, and biological networks. By studying communication dynamics, we can gain a better understanding of the transmission rules and the factors that influence the spread of information, rumors, and computer virus. Link prediction technology is a powerful tool for identifying potential connections within large-scale data, greatly facilitating research in social networks and scientific collaboration. Recommendation algorithms are designed to provide users with personalized content suggestions based on their interests and behaviors, enhancing the overall user experience. This session will bring together experts and scholars worldwide to discuss these cutting-edge topics' challenges and future directions, driving further breakthroughs in network learning and propagation dynamics.
Topics:
Trend analysis of social network information dissemination
Analysis of computer virus transmission process
Link prediction on social networks
Behavior analysis on social networks
Network state prediction
Pattern recognition of behaviors
Personalized recommender systems
Communication of SAGIN（Space-Air-Ground Integrated Network）
Special Session Ⅲ- Signal Processing, Access Techniques and Intelligence Algorithm for Communications (DDL: 2025.2.13)
Chair: Ying Lin, Lanzhou University of Technology, China
Co-chair: Suoping Li, Lanzhou University of Technology, China
Keywords:
Access Techniques
Artificial Intelligence
Signal Processing
Wireless Channel Modeling
Summary:
Communication signal processing, transmission, and access technologies are important parts of research in communication systems. In recent years, with the rise of artificial intelligence and intelligent algorithms, methodological research in communication signal processing and resource allocation has changed significantly. This session welcomes scholars to submit their latest academic research on the application of artificial intelligence to access technology, signal processing, and communication resource allocation.
Topics:
Orthogonal and non-orthogonal multiple access techniques
Radio Resource Management and Scheduling
Multiple-input multiple-output (MIMO) communication
Green communication and energy harvesting
Channel estimation and synchronization
Cooperative and relay-aided communications
UAV communication technology
Application of machine learning in communication system