Optimized machine learning model for air quality index prediction in major cities in India

SK Natarajan, P Shanmurthy, D Arockiam… - Scientific Reports, 2024 - nature.com
Industrial advancements and utilization of large amount of fossil fuels, vehicle pollution, and
other calamities increases the Air Quality Index (AQI) of major cities in a drastic manner …

[HTML][HTML] Air pollutant prediction based on ARIMA-WOA-LSTM model

J Luo, Y Gong - Atmospheric Pollution Research, 2023 - Elsevier
The problem of air pollution has always plagued people's lives, and the management of air
pollution cannot be achieved without the prediction and assessment of the concentration of …

State-of-art in modelling particulate matter (PM) concentration: A sco** review of aims and methods

L Gianquintieri, D Oxoli, EG Caiani… - Environment …, 2024 - Springer
Air pollution is the one of the most significant environmental risks to health worldwide. An
accurate assessment of population exposure would require a continuous distribution of …

[HTML][HTML] Hazard susceptibility map** with machine and deep learning: a literature review

AJ Pugliese Viloria, A Folini, D Carrion, MA Brovelli - Remote Sensing, 2024 - mdpi.com
With the increase in climate-change-related hazardous events alongside population
concentration in urban centres, it is important to provide resilient cities with tools for …

Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India

CB Pande, NL Kushwaha, OA Alawi, SS Sammen… - Environmental …, 2024 - Elsevier
This research was established to accurately forecast daily scale air quality index (AQI) which
is an essential environmental index for decision-making. Researchers have projected …

A new perspective on air quality index time series forecasting: A ternary interval decomposition ensemble learning paradigm

Z Wang, R Gao, P Wang, H Chen - Technological Forecasting and Social …, 2023 - Elsevier
Accurate forecasting of the air quality index (AQI) plays a crucial role in taking precautions
against upcoming air pollution risks. However, air quality may fluctuate greatly in a certain …

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates …

H Gholami, A Mohammadifar, RD Behrooz… - Environmental …, 2024 - Elsevier
Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality,
climate, ecosystems and human health. Therefore, measurements, prediction and …

Predicting air quality index using attention hybrid deep learning and quantum-inspired particle swarm optimization

AT Nguyen, DH Pham, BL Oo, Y Ahn, BTH Lim - Journal of big data, 2024 - Springer
Air pollution poses a significant threat to the health of the environment and human well-
being. The air quality index (AQI) is an important measure of air pollution that describes the …

[HTML][HTML] ADNNet: Attention-based deep neural network for Air Quality Index prediction

X Wu, X Gu, KW See - Expert Systems with Applications, 2024 - Elsevier
Abstract The Air Quality Index (AQI) is a crucial indicator for assessing the degree of
atmospheric pollution. Accurately forecasting AQI is notably challenging due to the …

Seasonal analysis of meteorological parameters and air pollutant concentrations in Kolkata: An evaluation of their relationship

NN Maltare, S Vahora, K Jani - Journal of Cleaner Production, 2024 - Elsevier
Air pollution and climate change present formidable global challenges, particularly in India,
where the average PM 2. 5 concentration in 2022 surpassed the WHO annual guideline …