Rainfall forecasting is one of the most challenging factors of weather forecasting all over the
planet. Due to climate change, Thailand has experienced extreme weather events, including …

Initiatives to minimise battery use, address sustainability, and reduce regular maintenance
have driven the challenge to use alternative power sources to supply energy to devices …

Abstract Machine learning (ML) methods have become an important tool for modelling and
forecasting complex high-dimensional spatiotemporal datasets such as those found in …

The prediction accuracy of hourly air temperature is generally poor because of random
changes, long time series, and the nonlinear relationship between temperature and other …

Air quality indicators and air quality index (AQI) prediction are effective approaches for urban
decision-makers, planners, managers and even city residents to arrange their risk …

In particular, predicting the temperature and humidity information plays a crucial role in
plantation, estimating rainfalls and climate change, and predicting air quality via specified …

Precise Air temperature modeling is crucial for a sustainable environment. In this study, a
novel binary optimized machine learning model, the random vector functional link (RVFL) …

Reliable weather forecasting is quite important for sectors with weather-dependent decision-
making. To capture unknown and complex dependencies from multiple spatiotemporal …

Buildings consume 74% of US electricity and 40% of primary energy use. However, 15% of
the energy was wasted due to bad controls. Many research studies have demonstrated that …

Abstract Study region Metropolitan Taipei city, Taiwan. Study focus The severity of climate
change in Taiwan is increasing, and the average temperature in Taiwan has increased by …