A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance
Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …
Prediction of water quality index (WQI) using support vector machine (SVM) and least square-support vector machine (LS-SVM)
The current calculations of water quality index (WQI) were sometimes can be very complex
and time-consuming which involves sub-index calculation like BOD and COD, however with …
and time-consuming which involves sub-index calculation like BOD and COD, however with …
Chemometrics for environmental monitoring: a review
Environmental monitoring is necessary to ensure the overall health and conservation of an
ecosystem. However, ecosystems (eg air, water, soil), are complex, involving numerous …
ecosystem. However, ecosystems (eg air, water, soil), are complex, involving numerous …
Prediction of air pollution index (API) using support vector machine (SVM)
WC Leong, RO Kelani, Z Ahmad - Journal of Environmental Chemical …, 2020 - Elsevier
The existing methods of calculating air pollution index are complex and time consuming.
Therefore new accurate and efficient modeling techniques need to be proposed. Thus, a …
Therefore new accurate and efficient modeling techniques need to be proposed. Thus, a …
Intelligent calibration and virtual sensing for integrated low-cost air quality sensors
This paper presents the development of air quality low-cost sensors (LCS) with improved
accuracy features. The LCS features integrate machine learning based calibration models …
accuracy features. The LCS features integrate machine learning based calibration models …
Fast identification and characterization of residual wastes via laser-induced breakdown spectroscopy and machine learning
B Yan, R Liang, B Li, J Tao, G Chen, Z Cheng… - Resources …, 2021 - Elsevier
Elemental composition and heating value are essential properties of residual wastes (RW)
for its energy utilization. This paper proposed a highly efficient approach to distinguish …
for its energy utilization. This paper proposed a highly efficient approach to distinguish …
[HTML][HTML] Evaluation of white-box versus black-box machine learning models in estimating ambient black carbon concentration
Air quality prediction with black-box (BB) modelling is gaining widespread interest in
research and industry. This type of data-driven models work generally better in terms of …
research and industry. This type of data-driven models work generally better in terms of …
Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder
A key challenge in building machine learning models for time series prediction is the
incompleteness of the datasets. Missing data can arise for a variety of reasons, including …
incompleteness of the datasets. Missing data can arise for a variety of reasons, including …
Air pollutant concentration forecast based on support vector regression and quantum-behaved particle swarm optimization
X Li, A Luo, J Li, Y Li - Environmental Modeling & Assessment, 2019 - Springer
In order to improve the forecasting accuracy of atmospheric pollutant concentration, a
prediction model of atmospheric PM 2.5 and nitrogen dioxide (NO 2) concentration based on …
prediction model of atmospheric PM 2.5 and nitrogen dioxide (NO 2) concentration based on …
A comparative analysis of Statistical and Computational Intelligence methodologies for the prediction of traffic-induced fine particulate matter and NO2
With the urbanization increase, urban mobility and transportation induce higher traffic
volumes causing environmental, economic and social impacts. This is due to continuous …
volumes causing environmental, economic and social impacts. This is due to continuous …