Air pollution, especially ground-level ozone, poses severe threats to human health and ecosystems. Accurate forecasting … forecast using a functional autoregressive model (FAR), where each daily ozone concentration profile is considered a single … functional datum. For comparison purposes, different traditional and machine learning techniques, such as autoregressive …

This study explores the stationary property of electricity consumption for Hunan province in China over the period … external shocks yield a permanent effect for electricity consumption in Hunan province. These findings shows that governments … should adopt policies to mitigate external shocks to electricity consumption in order to achieve electricity market stability …

the fitting ability of HAR models for electricity volatility forecasting at the daily horizon, whereas structural breaks … can improve the in-sample performance of HAR models when forecasting electricity volatility at daily, weekly, and monthly …. Considering day-of-the-week effects, structural breaks, or both, we propose three classes of HAR models to forecast electricity …

Short-term electricity price forecasting has received considerable attention in recent years. Despite this increased … electricity market (SEM). We utilized several forecasting approaches ranging from standard conditional volatility models to … interest, the literature lacks a concrete consensus on the most suitable forecasting approach. This study reports an extensive …