Machine learning-based time series models for effective CO2 emission prediction in India

China, India, and the USA are the countries with the highest energy consumption and CO 2 emissions globally. As per the report of datacommons.org , CO 2 emission in India is 1.80 metric tons per capita, which is harmful to living beings, so this paper presents India’s detrimental CO 2 emission effec...

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Veröffentlicht in:	Environmental science and pollution research international Jg. 30; H. 55; S. 116601 - 116616
Hauptverfasser:	Kumari, Surbhi, Singh, Sunil Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023 Springer Nature B.V
Schlagworte:	algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Autoregressive models Business metrics Carbon dioxide Carbon dioxide emissions China Comparative studies comparative study Deep learning Earth and Environmental Science Ecotoxicology Emission energy Energy consumption Environment Environmental Chemistry Environmental Health GIS Applied to Soil-Agricultural Health for Environmental Sustainability India Learning algorithms Long short-term memory Machine learning Mathematical models neural networks Performance measurement prediction Predictions Regression analysis Regression models Statistical analysis Statistical models Time series time series analysis Waste Water Technology Water Management Water Pollution Control India China Holt-Winters LSTM Linear regression Time series forecasting Random forest regressor Air pollution emissions
ISSN:	1614-7499, 0944-1344, 1614-7499
Online-Zugang:	Volltext
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