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description Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Authors:Shankar Subramaniam;
Naveenkumar Raju; Abbas Ganesan;Shankar Subramaniam
Shankar Subramaniam in OpenAIRENithyaprakash Rajavel;
+5 AuthorsNithyaprakash Rajavel
Nithyaprakash Rajavel in OpenAIREShankar Subramaniam;
Naveenkumar Raju; Abbas Ganesan;Shankar Subramaniam
Shankar Subramaniam in OpenAIRENithyaprakash Rajavel;
Nithyaprakash Rajavel
Nithyaprakash Rajavel in OpenAIREMaheswari Chenniappan;
Maheswari Chenniappan
Maheswari Chenniappan in OpenAIREChander Prakash;
Chander Prakash
Chander Prakash in OpenAIREAlokesh Pramanik;
Alokesh Pramanik
Alokesh Pramanik in OpenAIREAnimesh Kumar Basak;
Animesh Kumar Basak
Animesh Kumar Basak in OpenAIRESaurav Dixit;
Saurav Dixit
Saurav Dixit in OpenAIREdoi: 10.3390/su14169951
Air pollution is a major issue all over the world because of its impacts on the environment and human beings. The present review discussed the sources and impacts of pollutants on environmental and human health and the current research status on environmental pollution forecasting techniques in detail; this study presents a detailed discussion of the Artificial Intelligence methodologies and Machine learning (ML) algorithms used in environmental pollution forecasting and early-warning systems; moreover, the present work emphasizes more on Artificial Intelligence techniques (particularly Hybrid models) used for forecasting various major pollutants (e.g., PM2.5, PM10, O3, CO, SO2, NO2, CO2) in detail; moreover, focus is given to AI and ML techniques in predicting chronic airway diseases and the prediction of climate changes and heat waves. The hybrid model has better performance than single AI models and it has greater accuracy in prediction and warning systems. The performance evaluation error indexes like R2, RMSE, MAE and MAPE were highlighted in this study based on the performance of various AI models.
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more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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