Simulating daily PM2. 5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data
Q Guo, Z He, Z Wang - Chemosphere, 2023 - Elsevier
Accurate PM 2.5 concentrations predicting is critical for public health and wellness as well
as pollution control. However, traditional methods are difficult to accurately predict PM 2.5 …
as pollution control. However, traditional methods are difficult to accurately predict PM 2.5 …
Wavelets in combination with stochastic and machine learning models to predict agricultural prices
Wavelet decomposition in signal processing has been widely used in the literature. The
popularity of machine learning (ML) algorithms is increasing day by day in agriculture, from …
popularity of machine learning (ML) algorithms is increasing day by day in agriculture, from …
Impact from the evolution of private vehicle fleet composition on traffic related emissions in the small-medium automotive city
Understanding the emission characteristics in the evolution of private vehicle fleet
composition has become a key issue to be addressed to develop appropriate emission …
composition has become a key issue to be addressed to develop appropriate emission …
Prediction of heavy metals in airborne fine particulate matter using magnetic parameters by machine learning from a metropolitan city in China
H Xiao, X Qian, S Li, Y Liu, X Liu, H Li - Atmospheric Pollution Research, 2022 - Elsevier
This study explored a new statistical method for predicting airborne heavy metals using
environmental magnetism. Samples of fine particulate matter (PM 2.5) were collected for 1 …
environmental magnetism. Samples of fine particulate matter (PM 2.5) were collected for 1 …
Soil Moisture Monitoring and Evaluation in Agricultural Fields Based on NDVI Long Time Series and CEEMDAN
X Li, X Wang, J Wu, W Luo, L Tian, Y Wang, Y Liu… - Remote Sensing, 2023 - mdpi.com
The North China Plain is an important area for agricultural economic development in China.
But water shortages, severe groundwater over-exploitation and drought problems make it …
But water shortages, severe groundwater over-exploitation and drought problems make it …
Particulate matter forecasting using different deep neural network topologies and wavelets for feature augmentation
SLJ Galvão, JCO Matos, YKL Kitagawa, FS Conterato… - Atmosphere, 2022 - mdpi.com
The concern about air pollution in urban areas has substantially increased worldwide. One
of its main components, particulate matter (PM) with aerodynamic diameter of≤ 2.5 µm …
of its main components, particulate matter (PM) with aerodynamic diameter of≤ 2.5 µm …
A wide scale survey on weather prediction using machine learning techniques
S Kumari, P Muthulakshmi - Journal of Information & Knowledge …, 2023 - World Scientific
Several losses had been witnessed due to many natural calamities like earth quakes,
storms, cyclones, etc. These natural calamities have direct or indirect effects on the lives of …
storms, cyclones, etc. These natural calamities have direct or indirect effects on the lives of …
Hybrid extreme learning machine optimized bat algorithm based on ensemble empirical mode decomposition for modeling dissolved oxygen in river
In the present chapter, we use the empirical mode decomposition (EMD), the ensemble
EMD (EEMD), and the complete ensemble EMD with adaptive noise (CEEMDAN) for …
EMD (EEMD), and the complete ensemble EMD with adaptive noise (CEEMDAN) for …
Determining Effective Factors Regarding Weather and Some Types of Air Pollutants in Seasonal Changes of PM10 Concentration Using Tree-Based Algorithms in …
Z Ebrahimi-Khusfi… - Journal of …, 2024 - publish.kne-publishing.com
Introduction: This study was carried out with the aim of determining weather parameters and
air pollutants affecting seasonal changes of particulate matter of less than 10 microns (PM …
air pollutants affecting seasonal changes of particulate matter of less than 10 microns (PM …
Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and …
Z Ebrahimi-Khusfi, AR Nafarzadegan… - Environmental …, 2021 - Springer
This study aimed to evaluate the performance of multivariate adaptive regression splines
(MARS) and extremely randomized trees (ERT) models for predicting the internal and …
(MARS) and extremely randomized trees (ERT) models for predicting the internal and …