INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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.
Keywords:
Greenhouse Gas Emissions, Automobile Industry, Machine Learning, Regression
Cite Article:
"Prediction of Greenhouse Gas Emission in Cars using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 6, page no.763-769, June-2022, Available :http://www.ijnrd.org/papers/IJNRD2206088.pdf
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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
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