报告题目(Title): Data driven Causality Analysis – Systems Engineering Perspective
时间(Date&Time): 2018年1月29日14: 00
报告摘要(Abstract): Modern industries are awash with large amount of data. Extraction of information and knowledge discovery from data for control system design and system monitoring, from day by day routine process operating data, is interesting but challenging. There exist numerous challenging issues such as unknown causal relation, nonlinearity, non-Gaussian distributions, high dimensionality, collinearity, multiple modal operations, outlying points, missing measurement etc that must be considered during the information extraction process. The most fundamental problem is however the causal relation of data, knowledge of which is essential for data-based control design and fault diagnosis. This presentation will discuss concept of causality, existing algorithms, and state-of-the-art development of causality analysis from data along with future research directions.