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Local combustion regime identification using machine learning
- Source :
- Combustion Theory and Modelling. 26:135-151
- Publication Year :
- 2021
- Publisher :
- Informa UK Limited, 2021.
-
Abstract
- A new combustion regime identification methodology using the neural networks as supervised classifiers is proposed and validated. As a first proof of concept, a binary classifier is trained with la...
- Subjects :
- Artificial neural network
Computer science
business.industry
General Chemical Engineering
General Physics and Astronomy
Energy Engineering and Power Technology
General Chemistry
Gradient-free regime classification
multi-regime reacting flows
neural networks
tribrachial flames
Combustion
Machine learning
computer.software_genre
Identification (information)
ComputingMethodologies_PATTERNRECOGNITION
Fuel Technology
Binary classification
Proof of concept
Modeling and Simulation
Artificial intelligence
business
computer
Subjects
Details
- ISSN :
- 17413559 and 13647830
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Combustion Theory and Modelling
- Accession number :
- edsair.doi.dedup.....ece9ac21208c940dbf5eeb528188cae8
- Full Text :
- https://doi.org/10.1080/13647830.2021.1991595