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Linear Regression model to predict the Value of Gas Emitted from Vehicle
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 31 |
| Year of Publication: 2022 |
| Authors: Israa Abdulrauof Othman |
10.5120/ijca2022922386
|
Israa Abdulrauof Othman . Linear Regression model to predict the Value of Gas Emitted from Vehicle. International Journal of Computer Applications. 184, 31 ( Oct 2022), 43-48. DOI=10.5120/ijca2022922386
Abstract
Global warming, jeopardizes the national security, endangers health and threatens other basic human needs. Some impacts such as rising seas, record high temperatures, and severe droughts and flooding are already increasingly common. Unfortunately, oil related emissions may rise in the coming years as refines “unconventional” oils, such as tight oil and tar sands and the oil industry extracts. Avoiding unnecessary emission from the oil we do use and using less oil is the real solution. This paper presents the application of machine learning model using linear regression techniques to supply fuel consumption of vehicles to a large dataset from IBM. The model gives:Mean Absolute Error (MAE) =22.78, residual sum square (RSS) =917.55, R2 score=0.067. The results contribute to the quantifying process of energyair pollution and cost caused by transportation, followed by proposing relevant recommendations for bothproducers and vehicle users. Future effort should aim towards developing larger datasets for building APIs and applications and higher performancemodels.
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