Marjan Momtazpour, Jinghe Zhang, Saifur Rahman, Ratnesh Sharma, Naren Ramakrishnan
The analysis of large scale data logged from complex cyber-physical systems, such as microgrids, often entails the discovery of invariants capturing functional as well as operational relationships underlying such large systems. We describe a latent factor approach to infer invariants underlying system variables and how we can leverage these relationships to monitor a cyber-physical system. In particular we illustrate how this approach helps rapidly identify outliers during system operation.
- Date of publication:
- September 16, 2015
- SIGKDD international conference on Knowledge discovery and data mining
- Association for Computing Machinery (ACM)
- Page number(s):