Xiaoshan Wang

Title: Xiaoshan Wang and Collaborative Project Disaster Warning

Introduction

Xiaoshan Wang is an inventor based in Qingdao, China, and is associated with Qingdao University of Technology. His work includes a patented method and system for assessing disaster risks in project structures by combining monitoring data from multiple physical fields.

Latest Patents

Wang is credited with 1 patent: “Project Disaster Warning Method and System Based on Collaborative Fusion of Multi-Physics Monitoring Data.” The invention processes real-time data from multiple sensors monitoring potentially dangerous parts of a project structure. It normalizes time-series measurements, uses multivariate statistical analysis to assess how different monitoring indicators relate to structural safety, and applies those sensitivity results to guide the initialization and training of a long short-term memory (LSTM) network. The network’s outputs are then fused using an improved Dempster–Shafer evidence theory based on Chebyshev distance. Finally, a decision method using basic probability assignments determines the disaster danger level of the monitored areas.

Career Highlights

Wang’s patent addresses the challenge of interpreting diverse monitoring signals together when evaluating potential hazards in project structures. By combining statistical analysis, LSTM-based modeling, and evidence fusion, the proposed system aims to support more integrated disaster warnings.

Collaborations

Wang’s listed coworkers include Liming Zhang and Zhongyuan Liu. His work is associated with Qingdao University of Technology.

Conclusion

Xiaoshan Wang’s patented approach brings together multi-sensor monitoring, machine learning, and evidence-based decision-making to assess disaster risks in project structures.