Optimal Prediction of Air Quality Index in Metropolitan Cities Using Fuzzy Time Series with Deep Learning Approach

Optimal Prediction of Air Quality Index in Metropolitan Cities Using Fuzzy Time Series with Deep Learning Approach

The advancement of science and technology has led to the custom of industry, transportation, and other sectors to release a great amount of pollutants into the atmosphere, causing air pollution. Predicting the Air Quality Index (AQI) with high accuracy is just as crucial as predicting the weather. T...

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Bibliographic Details
Main Authors: Asha Unnikrishnan, Subramanian Rajeswari
Format: Article
Language:English
Published: Polish Society of Ecological Engineering (PTIE) 2024-01-01
Series:Ecological Engineering & Environmental Technology
Subjects:
sarima
deep learning
air quality index
northern and southern cities
stochastic fuzzy time series
temporal convolution network
Online Access:http://www.ecoeet.com/Optimal-Prediction-of-Air-Quality-Index-in-Metropolitan-Cities-Using-Fuzzy-Time-Series,175720,0,2.html

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http://www.ecoeet.com/Optimal-Prediction-of-Air-Quality-Index-in-Metropolitan-Cities-Using-Fuzzy-Time-Series,175720,0,2.html

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