Development of new hybrid model of discrete wavelet decomposition and autoregressive integrated moving average (ARIMA) models in application to one month …
Everywhere around the globe, the hot topic of discussion today is the ongoing and fast-
spreading coronavirus disease (COVID-19), which is caused by the severe acute respiratory …
spreading coronavirus disease (COVID-19), which is caused by the severe acute respiratory …
Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries
Discussions about the recently identified deadly coronavirus disease (COVID-19) which
originated in Wuhan, China in December 2019 are common around the globe now. This is …
originated in Wuhan, China in December 2019 are common around the globe now. This is …
Characteristic and driving factors of aerosol optical depth over mainland China during 1980–2017
Since the reform and opening up of China, the increasing aerosol emissions have posted
great challenges to the country's climate change and human health. The aerosol optical …
great challenges to the country's climate change and human health. The aerosol optical …
Three decades of gross primary production (GPP) in China: Variations, trends, attributions, and prediction inferred from multiple datasets and time series modeling
The accurate estimation of gross primary production (GPP) is crucial to understanding plant
carbon sequestration and grasping the quality of the ecological environment. Nevertheless …
carbon sequestration and grasping the quality of the ecological environment. Nevertheless …
Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models
This study investigates the applicability of three different soft computing methods, least
square support vector regression (LSSVR), multivariate adaptive regression splines …
square support vector regression (LSSVR), multivariate adaptive regression splines …
Soft computing model coupled with statistical models to estimate future of stock market
Almost every organization around the globe is working with uncertainty due to inevitable
changes and growth in every sphere of life. These changes affect directly or indirectly the …
changes and growth in every sphere of life. These changes affect directly or indirectly the …
Estimation of PM2.5 Concentration across China Based on Multi-Source Remote Sensing Data and Machine Learning Methods
Y Yang, Z Wang, C Cao, M Xu, X Yang, K Wang… - Remote Sensing, 2024 - mdpi.com
Long-term exposure to high concentrations of fine particles can cause irreversible damage
to people's health. Therefore, it is of extreme significance to conduct large-scale continuous …
to people's health. Therefore, it is of extreme significance to conduct large-scale continuous …
A comparative time series analysis and modeling of aerosols in the contiguous United States and China
Long-term trend analysis and modeling of aerosol distribution is of paramount importance to
study radiative forcing, climate change, and human health. Previous studies on …
study radiative forcing, climate change, and human health. Previous studies on …
Variability, predictability, and uncertainty in global aerosols inferred from gap-filled satellite observations and an econometric modeling approach
Time series analyses and stochastic modeling assessments of aerosols are critical for
climate change and human health studies. However, the precise characterization of the …
climate change and human health studies. However, the precise characterization of the …
Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation
Human activities-related aerosol emissions and CO 2 emissions originate from many of the
common sources. Identifying the aerosol variations and the underling determinates can …
common sources. Identifying the aerosol variations and the underling determinates can …