Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …

Industrial control systems (ICSs) are widely used and vital to industry and society. Their
failure can have severe impact on both the economy and human life. Hence, these systems …

In this research, monthly wind speed time series of the Kirsehir was investigated using the
stand-alone, hybrid and ensemble models. The artificial neural networks, Gaussian process …

Triboelectric nanogenerator (TENG) provides a new idea for harvesting low-frequency
energy tire-road interaction and self-powered sensors. A real-time assessment of skid …

Climate change and increasing water demands underscore the importance of water
resource management. Precise precipitation forecasting is critical to effective management …

Accurate and efficient runoff simulations are crucial for water management in basins.
Rainfall-runoff simulation approaches range between physical, conceptual, and data-driven …

Elucidating the biophysical mechanisms governing the exchange of water vapor between
land and the atmosphere is particularly crucial for addressing water scarcity under climate …

In this study, we develop and test a local rainfall (precipitation) prediction system based on
artificial neural networks (ANNs). Our system can automatically obtain meteorological data …

Handling missing values is a critical component of the data processing in hydrological
modeling. The key objective of this research is to assess statistical techniques (STs) and …

Existing forecasting methods employed for rainfall forecasting encounter many limitations,
because the difficulty of the underlying mathematical proceeding in dealing with the …