The prediction model's performance in view of the wavelet transform (WT) is affected
because the wavelet basis function (WBF) and its orders and layers are determined …

Many recent studies propose wavelet-based hydrological and water resources forecasting
models that have been incorrectly developed and that cannot properly be used for real …

Hydrometeorological disasters, including floods and droughts, have intensified in both
frequency and severity in recent years. This trend underscores the critical role of timely …

Improving forecasting techniques for streamflow time series is of extreme importance for
water resource planning. Among the available techniques, those based on machine …

Advancement in river flow prediction systems can greatly empower the operational river
management to make better decisions, practices, and policies. Machine learning methods …

Developing hydrologic models based on data-driven approaches (DDA) is very complicated
due to the complex nature of meteorological data. For example, a high degree of …

Accurate modeling for nonlinear and nonstationary rainfall-runoff processes is essential for
performing hydrologic practices effectively. This paper proposes two hybrid machine …

Hourly river flow pattern monitoring and simulation is the indispensable precautionary task
for river engineering sustainability, water resource management, flood risk mitigation, and …

Accurate prediction of daily streamflow plays an essential role in various applications of
water resources engineering, such as flood mitigation and urban and agricultural planning …

Mental fatigue in drivers is one of the leading causes that give rise to traffic accidents.
Electroencephalography (EEG)-based driving fatigue studies showed promising …