Detection and quantification of temperature sensor drift using probabilistic neural networks

Expert Systems with Applications（2023）

引用 5|浏览27

暂无评分

摘要

•New machine learning method for detection of long-term temperature sensor drift.•New anomaly detection method based on the trinomial distribution.•Data-driven prediction of temperature in concrete structures is greatly improved.•The method was successfully tested on 7-years data of a real structure.

查看译文

关键词

Long-term structural health monitoring,Data validation,Temperature sensor drift,Fiber optics,Machine learning,Probabilistic neural networks,Data-driven prediction,Temperature prediction,Anomaly detection

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要