Using of Support Vector Machine (SVM), Gradient Boosting (GB) and Artificial Neural Network (ANN) Techniques in Internal Combustion Engine Tests: A Review

Year 2021, Volume: 2 Issue: 1, 1 - 9, 24.03.2021

Mehmet Bilban , Mehmet Selman Gökmen

Abstract

As a result of the literature review, it is seen that researchers tend to use alternative machine learning methods in order to determine the complex relationship between engine performance data, diesel-biodiesel fuel mixture ratios and exhaust emissions. As a result of the researches, it was observed that gradient boosting algorithm, support vector machine and artificial neural network machine learning methods are frequently used methods. Among these three methods, it was concluded that the method that has been the subject of the studies and stated to improve the results at an optimum level is the artificial neural network. In this study, the gradient boosting algorithm, support vector machine and artificial neural network methods are discussed and the reasons for using the artificial neural network method more than the other methods are investigated.

Keywords

artificial neural network, gradient boosting, machine learning, support vector machine, internal combustion engines

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