Prediction of Diesel Engine Performance using Support Vector Regression Technique
Aakash Jannumahanthi1, Sivanesan Murugesan2
1Aakash Jannumahanthi, Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.
2Sivanesan Murugesan, Department of Mechanical Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.
Manuscript received on July 10, 2020. | Revised Manuscript received on July 26, 2020. | Manuscript published on August 10, 2020. | PP: 260-264 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J74940891020 | DOI: 10.35940/ijitee.J7494.0891020
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Abstract: Extensive research has been carried out on the prediction of diesel engine performance. Machine learning techniques such as support vector regression technique makes the performance predictions simpler. Support vector regression is a regression algorithm used to minimize the error with a threshold value and tries to fit the best line with a threshold value. In this paper, a detailed study of diesel engine performance using support vector regression and performance metrics such as brake thermal efficiency and accuracy are explored. Findings specify that support vector regression is an efficient technique for diesel engine performance that validates and compares the actual performance with high accuracy. For engine performance, the support vector machine supports to reduce the time and cost of testing.
Keywords: Support Vector Regression, Engine Performance, Brake thermal efficiency.
Scope of the Article: Support Vector Regression