Accurate and reliable short-term forecasting of wind power is vital for balancing energy and
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …

In response to growing concerns surrounding the relationship between climate change and
escalating flood risk, there is an increasing urgency to develop precise and rapid flood …

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

Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …

Urban pluvial floods induced by rainstorms can cause severe losses to human lives and
property. Fast and accurate simulation and prediction of urban pluvial flood are of …

There exists a substantial disparity in the distribution of streamflow gauge and basin
characteristic information, with a majority of flood observations being recorded from a limited …

This study provides an extensive review of over 200 journal papers focusing on Machine
Learning (ML) algorithms' use for promoting a sustainable management of the marine and …

This study assessed water quality (WQ) in Tongi Canal, an ecologically critical and
economically important urban canal in Bangladesh. The researchers employed the Root …

Accurate prediction of wave overtop** at sea defences remains central to the protection of
lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased …

The impacts of climate change, especially sea-level rise, are an increasing threat to the
world's coastal regions. Following recommendations made by the United Nations about the …