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Accelerated multiple alarm flood sequence alignment for abnormality pattern mining
- Source :
- Journal of Process Control. 82:44-57
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Alarm floods can interfere with operators and may therefore cause or aggravate industrial accidents. A novel algorithm is proposed for pattern mining in multiple alarm floods. Unlike traditional methods which either cannot deal with multiple sequences with time stamps or suffer from high computational cost, the computational complexity of this proposed algorithm is reduced significantly by introducing a generalized pairwise sequence alignment method and a progressive multiple sequence alignment approach. Two types of alignment refinement methods are developed to improve the alignment accuracy. The effectiveness of the proposed algorithm is tested using a dataset from a real chemical plant.
- Subjects :
- 0209 industrial biotechnology
Multiple sequence alignment
Computational complexity theory
Flood myth
business.industry
Computer science
Sequence alignment
Pattern recognition
02 engineering and technology
Industrial and Manufacturing Engineering
Computer Science Applications
ALARM
020901 industrial engineering & automation
020401 chemical engineering
13. Climate action
Control and Systems Engineering
Modeling and Simulation
Pairwise sequence alignment
Artificial intelligence
0204 chemical engineering
Abnormality
business
Subjects
Details
- ISSN :
- 09591524
- Volume :
- 82
- Database :
- OpenAIRE
- Journal :
- Journal of Process Control
- Accession number :
- edsair.doi...........bdf4dc21b9eb6a43d269c81ba6876d0a