Building a Predictive Model to Estimate NOx Emission Pollutant of Backhoe Equipment

DOI

10.2991/icoemis-19.2019.37How to use a DOI?

Keywords

NOx, Support Vector Machine Model, SVM

Abstract

NOx is one of emission pollutant resulted from Backhoe equipment. This research aims to build a predictive model to estimate NOx pollutant released by backhoe equipment using Support Vector Machine model. Two type of kernel types (radial basis function and linear kernel types) are compared. The study runs the model several time to maximize the accuracy of SVM by finding the optimized parameter, which includes C, ε, and γ. The results show that radial basis function kernel type provides higher accuracy than linear kernel type. In addition, this study also concludes that higher C and γ parameter results in much lower mean absolute error value. However, it requires much longer calculation time. The SVM predictive model also show that the significant factors to predict NOx emission are MAP, RPM, backhoe type and the intake temperature.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Aisyah Larasati
AU  - Aal Mahardika
AU  - Darin Ramadhanti
AU  - Yuh-Wen Chen
AU  - Apif Hajji
AU  - Vertic Darmawan
PY  - 2019/11
DA  - 2019/11
TI  - Building a Predictive Model to Estimate NOx Emission Pollutant of Backhoe Equipment
BT  - Proceedings of the 2019 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019)
PB  - Atlantis Press
SP  - 268
EP  - 274
SN  - 1951-6851
UR  - https://doi.org/10.2991/icoemis-19.2019.37
DO  - 10.2991/icoemis-19.2019.37
ID  - Larasati2019/11
ER  -