River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …

Precise streamflow prediction is necessary for better planning and managing available
water and future water resources, especially for high altitude mountainous glacier melting …

For accurate estimation of streamflow of a mountainous river basin, a novel hybrid method is
developed in this study, where gradient-based optimization (GBO) algorithm is employed to …

Precise long-term streamflow prediction has always been important in the hydrology field,
and has provided essential information for efficient water-resource management and …

River flow variations directly affect the hydro-climatological, environmental, and ecological
characteristics of a region. Therefore, an accurate prediction of river flow can critically be …

Accurate predictions of significant wave heights are important for a number of maritime
applications, such as design of coastal and offshore structures. In the present study, an …

Carbonate petroleum reservoirs typically have lower permeabilities and recovery factors
than sandstone reservoirs, so the natural fractures they often incorporate have positive …

In multivariate time series forecasting tasks, expanding forecast length and improving
forecast efficiency is an urgent need for practical applications. Accurate long-term …

Precise streamflow estimation plays a key role in optimal water resource use, reservoirs
operations, and designing and planning future hydropower projects. Machine learning …