Air pollution and its health impacts in Malaysia: a review
RSA Usmani, A Saeed, AM Abdullahi, TR Pillai… - Air Quality, Atmosphere …, 2020 - Springer
Air pollution is strongly tied to climate change. Industrialization and fossil fuel combustion
are the main contributors leading to climate change, also being significant sources of air …
are the main contributors leading to climate change, also being significant sources of air …
Water pollution examination through quality analysis of different rivers: a case study in India
Restoration of water quality at rivers is a big problem for water quality managers. This paper
analyzes water quality parameters across five years from 2012 to 2016 in a case study of …
analyzes water quality parameters across five years from 2012 to 2016 in a case study of …
Fuzzy logic based smart irrigation system using internet of things
Traditional agricultural systems require huge amount of power for field watering. This paper
proposes a smart irrigation system that helps farmers water their agricultural fields using …
proposes a smart irrigation system that helps farmers water their agricultural fields using …
[HTML][HTML] A statistical learning framework for spatial-temporal feature selection and application to air quality index forecasting
Accurate air quality index (AQI) forecasting makes a difference to public health, local
economic development, and ecological environment. As a typical geographical datum, the …
economic development, and ecological environment. As a typical geographical datum, the …
A performance comparison study on PM2. 5 prediction at industrial areas using different training algorithms of feedforward-backpropagation neural network (FBNN)
P Chinatamby, J Jewaratnam - Chemosphere, 2023 - Elsevier
Presence of particulate matters with aerodynamic diameter of less than 2.5 μm (PM 2.5) in
the atmosphere is fast increasing in Malaysia due to industrialization and urbanization …
the atmosphere is fast increasing in Malaysia due to industrialization and urbanization …
[PDF][PDF] Optimization of Markov weighted fuzzy time series forecasting using genetic algorithm (GA) and particle swarm optimization (PSO)
Abstract The Markov Weighted Fuzzy Time Series (MWFTS) is a method for making
predictions based on developing a fuzzy time series (FTS) algorithm. The MWTS has …
predictions based on developing a fuzzy time series (FTS) algorithm. The MWTS has …
Hyperautomation for air quality evaluations: A perspective of evidential three-way decision-making
J Ding, C Zhang, D Li, AK Sangaiah - Cognitive Computation, 2023 - Springer
Hyperautomation acts as a real digital transformation with the support of several cutting-
edge cognitive computation methods that include robotic process automation, natural …
edge cognitive computation methods that include robotic process automation, natural …
Novel hybrid extreme learning machine and multi-objective optimization algorithm for air pollution prediction
L Bai, Z Liu, J Wang - Applied Mathematical Modelling, 2022 - Elsevier
A novel system regarding deterministic and interval predictions of pollutant concentration is
constructed in this study, which can not only obtain higher prediction accuracy in …
constructed in this study, which can not only obtain higher prediction accuracy in …
[HTML][HTML] A new hybrid fuzzy time series model with an application to predict PM10 concentration
Fuzzy time series (FTS) forecasting models show a great performance in predicting time
series, such as air pollution time series. However, they have caused major issues by utilizing …
series, such as air pollution time series. However, they have caused major issues by utilizing …
Multi-horizon air pollution forecasting with deep neural networks
Air pollution is a global problem, especially in urban areas where the population density is
very high due to the diverse pollutant sources such as vehicles, industrial plants, buildings …
very high due to the diverse pollutant sources such as vehicles, industrial plants, buildings …