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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21508
Article Published : 8513
Total Authors : 22399
Total Reviewer : 805
Total Countries : 158
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| Paper Title: | A Review on Predicts Emission of Greenhouse Gases Using ML |
| Authors Name: | Apeksha K Gowda , Dr. Geetha S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_182633
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| Published Paper Id: | IJRTI2206280 |
| Published In: | Volume 7 Issue 6, June-2022 |
| DOI: | |
| Abstract: | The environment is under increased threat due to the rapid increase in GHG (Greenhouse Gas) emission. The effects of change of climate on the planet's inhabitants include an increase in heat and temperature at the surface of the earth, a rise in sea levels, and direct effects on human health such heat stress and other heat-related illnesses. Researchers have suggested a variety of strategies for predicting GHG emission; however machine learning-based approaches using gas feature input vectors appear to have the best software reliability, operating excellence, and prediction accuracy. We examined various greenhouse gases that are released from various sectors in this paper, examined various feature sources, reviewed machine learning approaches for forecasting the production of greenhouse gases, looked at the benefits and drawbacks of these approaches, and talked about the field's future directions. The numerous machine learning methods for predicting greenhouse gas emissions, which can then be used for analysis, will be discussed in this study. |
| Keywords: | Machine Learning, Prediction, Greenhouse gases (GHG). |
| Cite Article: | "A Review on Predicts Emission of Greenhouse Gases Using ML", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.1869 - 1874, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206280.pdf |
| Downloads: | 000205245 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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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Published Paper ID: IJRTI2206280
Registration ID:182633
Published In: Volume 7 Issue 6, June-2022
DOI (Digital Object Identifier):
Page No: 1869 - 1874 Country: Bengaluru, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2206280 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2206280 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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