This study presents a novel application of machine learning to deliver optimised, multi-
model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify …

Local scouring around the piers of a bridge is the one of the major reasons for bridge failure,
potentially resulting in heavy losses in terms of both the economy and human life. Prediction …

Prediction of bridge pier scour depth is essential for safe and economical bridge design.
Kee** in mind the complex nature of bridge scour phenomenon, there is a need to …

The selective pattern matching method for forecasting the increment signs of financial time
series is proposed. This approach is based on indexing the time series to find similar sites in …

The intelligent system applications require automated data-driven modeling tools. The
performance consistency of modeling tools is very essential to reduce the need for human …

Extensive research has been carried out to predict bridge pier scour, with laboratory and
field data, using different modelling techniques. This study introduces a new soft computing …

In recent decades, Artificial Intelligence (AI) has become an essential tool for modeling and
forecasting in different research fields. Mechanical engineering is no exception because …

Due to uncertainties associated with ensembles of global hydrological models (GHMs), their
arithmetic mean (ensemble mean, EM) is normally used to report the projected hydrological …

Modeling the precipitation evolution at a regional scale is a topic of interest in order to
predict the weather evolution and climate change, with their multiple consequences, in a …

In this article we describe the regional evolution of precipitation in Dobrudja, a region
situated in the South–East of Romania, using the mean annual precipitation collected from …