Autoregressive models in environmental forecasting time series: a theoretical and application review
Though globalization, industrialization, and urbanization have escalated the economic
growth of nations, these activities have played foul on the environment. Better understanding …
growth of nations, these activities have played foul on the environment. Better understanding …
Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability
This study provides a new comparative analysis of four hybrid artificial intelligence models
for the spatially explicit prediction of wildfire probabilities. Each model consists of an …
for the spatially explicit prediction of wildfire probabilities. Each model consists of an …
A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine
The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the
difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model …
difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model …
Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain
Air pollution, and especially atmospheric particulate matter (PM), has a profound impact on
human mortality and morbidity, environment, and ecological system. Accordingly, it is very …
human mortality and morbidity, environment, and ecological system. Accordingly, it is very …
Spatiotemporal informer: A new approach based on spatiotemporal embedding and attention for air quality forecasting
Y Feng, JS Kim, JW Yu, KC Ri, SJ Yun, IN Han… - Environmental …, 2023 - Elsevier
Accurate prediction of air pollution is essential for public health protection. Air quality,
however, is difficult to predict due to the complex dynamics, and its accurate forecast still …
however, is difficult to predict due to the complex dynamics, and its accurate forecast still …
A hybrid CNN-Transformer model for ozone concentration prediction
Ozone concentration has come to the fore as an important air quality indicator. However,
ozone concentrations vary with meteorological conditions and the presence of other …
ozone concentrations vary with meteorological conditions and the presence of other …
A novel hybrid forecasting scheme for electricity demand time series
R Li, P Jiang, H Yang, C Li - Sustainable Cities and Society, 2020 - Elsevier
Electricity demand/load forecasting always plays a vital role in the management and
operation of power systems, since it can help develop an optimal action program for power …
operation of power systems, since it can help develop an optimal action program for power …
Selection of key features for PM2. 5 prediction using a wavelet model and RBF-LSTM
YC Chen, DC Li - Applied Intelligence, 2021 - Springer
PM2. 5 prediction has received much attention from researchers in recent years, as PM2. 5
has been proven to have a major impact on human health. High-precision PM2. 5 …
has been proven to have a major impact on human health. High-precision PM2. 5 …
Prediction algorithm of PM2. 5 mass concentration based on adaptive BP neural network
Y Chen - Computing, 2018 - Springer
Abstract PM2. 5 hadn't received much attention until 2013 when people started to
understand its dreadful impacts to human health. According to the meteorological monitoring …
understand its dreadful impacts to human health. According to the meteorological monitoring …
ARIMA analysis of the effect of land surface coverage on PM10 concentrations in a high-altitude megacity
This paper uses ARIMA models for daily temporal analysis of the effect of land surface
coverage (LSC) on PM 10 concentrations in a high-altitude megacity. Bogota, the capital of …
coverage (LSC) on PM 10 concentrations in a high-altitude megacity. Bogota, the capital of …