Spatiotemporal air quality forecasting and health risk assessment over smart city of NEOM
Modeling and predicting air pollution concentrations is important to provide early warnings
about harmful atmospheric substances. However, uncertainty in the dynamic process and …
about harmful atmospheric substances. However, uncertainty in the dynamic process and …
A space-embedding strategy for anomaly detection in multivariate time series
Anomaly detection of time series has always been a hot topic in academia and industry.
However, many existing multivariant time series methods suffer from common challenges …
However, many existing multivariant time series methods suffer from common challenges …
[HTML][HTML] Data-driven modeling of multimode chemical process: Validation with a real-world distillation column
Real-world industrial processes frequently operate in different modes such as start-up,
transient, and steady-state operation. Since different operating modes are governed by …
transient, and steady-state operation. Since different operating modes are governed by …
Seasonal solar irradiance forecasting using artificial intelligence techniques with uncertainty analysis
V Gayathry, D Kaliyaperumal, SR Salkuti - Scientific Reports, 2024 - nature.com
Renewable integration in utility grid is crucial in the current energy scenario. Optimized
utilization of renewable energy can minimize the energy consumption from the grid. This …
utilization of renewable energy can minimize the energy consumption from the grid. This …
Short-Term Forecasting of Electric Vehicle Load Using Time Series, Machine Learning, and Deep Learning Techniques
Electric vehicles (EVs) are inducing revolutionary developments to the transportation and
power sectors. Their innumerable benefits are forcing nations to adopt this sustainable …
power sectors. Their innumerable benefits are forcing nations to adopt this sustainable …
Assessment of seasonal variability of PM, BC and UFP levels at a highway toll stations and their associated health risks
AK Patra, SSR Kolluru, A Penchala, S Kumar… - Environmental …, 2024 - Elsevier
As a part of their occupation, workers at toll stations are exposed to traffic emissions during
the working shift, which sometimes stretches to 12 h. To assess the exposure and …
the working shift, which sometimes stretches to 12 h. To assess the exposure and …
Determinants of traffic related atmospheric particulate matter concentrations and their associated health risk at a highway toll plaza in India
People working at toll plazas are continuously exposed to high pollutant concentrations due
to traffic congestion at toll booths. However, there are fewer studies available which focus on …
to traffic congestion at toll booths. However, there are fewer studies available which focus on …
Novel MIA-LSTM Deep Learning Hybrid Model with Data Preprocessing for Forecasting of PM2.5
Day by day pollution in cities is increasing due to urbanization. One of the biggest
challenges posed by the rapid migration of inhabitants into cities is increased air pollution …
challenges posed by the rapid migration of inhabitants into cities is increased air pollution …
[HTML][HTML] Uncertainty analysis of different forecast models for wind speed forecasting
Time-ahead forecasting of renewable energy resources is essential for successful planning
and operation of renewable integrated micro grids. Numerous studies have focused on wind …
and operation of renewable integrated micro grids. Numerous studies have focused on wind …
A probabilistic framework for identifying anomalies in urban air quality data
Just as the value of crude oil is unlocked through refining, the true potential of air quality
data is realized through systematic processing, analysis, and application. This refined data …
data is realized through systematic processing, analysis, and application. This refined data …