Short-term rainfall forecasting plays an important role in hydrologic modeling and water
resource management problems such as flood warning and real time control of urban …

Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …

This study proposes novel integration of extreme learning machine (ELM) and adaptive
neuro swarm intelligence (ANSI) techniques for the determination of California bearing ratio …

Monthly prediction of streamflow is a fundamental and complex hydrological phenomenon.
Accurate streamflow prediction helps in water resources planning, design, and …

The study proposes an improved Harris hawks optimization (IHHO) algorithm by integrating
the standard Harris hawks optimization (HHO) algorithm and mutation-based search …

This study implements a hybrid ensemble machine learning method for forecasting the rate
of penetration (ROP) of tunnel boring machine (TBM), which is becoming a prerequisite for …

Coefficient of consolidation (Cv) is an important parameter in the designing of civil
engineering structures founded on soil. Determination of the Cv in the laboratory is beset …

Prediction of long-term rainfall patterns is a highly challenging task in the hydrological field
due to random nature of rainfall events. The contribution of monthly rainfall is important in …

This study proposes a high-performance machine learning model to sidestep the time of
conducting actual laboratory tests of soil compression index (C c), one of the important …

Real-time and short-term prediction of river flow is essential for efficient flood management.
To obtain accurate flow predictions, a reliable rainfall-runoff model must be used. This study …