Prediction of Greenhouse Gas Emission in Cars using Machine Learning

Prediction of Greenhouse Gas Emission in Cars using Machine Learning

Registration ID: IJNRD_181832

Published ID: IJNRD2206088

DOI: Click Here to Get

Amit A Bhalerao , Dr. Shantakumar B Patil

Greenhouse Gas Emissions, Automobile Industry, Machine Learning, Regression

Automobile industry is one of the biggest sources of emission of a major Greenhouse Gas i.e., CO2 (Carbon-Dioxide). Unless transport emissions are monitored and brought under control, national and international climate goals will be missed. To meet commitments, we need to track emissions from automobiles and build technologies that would help us to decarbonize them effectively. We need every tool to tackle CO2 emissions from automobiles and early prediction of such emissions using statistical data can help people across the globe in aiding transformative changes that might end up delivering requisite huge cuts in emission. The project aims at predicting CO2 emission levels by analyzing dataset containing official record of statistical data from various car makers. The concept of Regression under Machine Learning is implemented to predict the emission rate and a final study of overall analysis is carried out to determine the best means of predicting rate(s) of emission.

Published Paper   E-Certificate

"Prediction of Greenhouse Gas Emission in Cars using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.7, Issue 6, page no.763-769, June-2022, Available :https://ijnrd.org/papers/IJNRD2206088.pdf

Volume 7 Issue 6, June-2022

Pages : 763-769

Paper Reg. ID: IJNRD_181832

Published Paper Id: IJNRD2206088

Downloads: 000121178

Research Area: Computer Science & Technology 

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2206088.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2206088

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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