SVM and ANFIS for Prediction of Performance and Exhaust Emissions of a SI Engine with Gasoline–Ethanol Blended Fuels
This paper studies the use of support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and the exhaust emissions of a spark ignition (SI) engine, which operates on ethanol–gasoline blends of 0%, 5%, 10%, 15% and 20% called E0, E5, E10, E15...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/11655/ http://umpir.ump.edu.my/id/eprint/11655/ http://umpir.ump.edu.my/id/eprint/11655/ http://umpir.ump.edu.my/id/eprint/11655/1/SVM%20and%20ANFIS%20for%20Prediction%20of%20Performance%20and%20Exhaust%20Emissions%20of%20a%20SI%20Engine%20with%20Gasoline%E2%80%93Ethanol%20Blended%20Fuels.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/11655/http://umpir.ump.edu.my/id/eprint/11655/
http://umpir.ump.edu.my/id/eprint/11655/
http://umpir.ump.edu.my/id/eprint/11655/1/SVM%20and%20ANFIS%20for%20Prediction%20of%20Performance%20and%20Exhaust%20Emissions%20of%20a%20SI%20Engine%20with%20Gasoline%E2%80%93Ethanol%20Blended%20Fuels.pdf