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 …

In this study, the main objective is to develop and compare several advanced Artificial
Intelligent (AI) models namely Adaptive Network based Fuzzy Inference System optimized …

Neural networks and genetic algorithms are the two sophisticated machine learning
techniques presently attracting attention from scientists, engineers, and statisticians, among …

Persistent risks of extreme weather events including droughts and floods due to climate
change require precise and timely rainfall forecasting. Yet, the naturally occurring non …

Seasonal rainfall forecasting is important for water resources management, agriculture, and
disaster prevention. Our study aims to provide an automated deep learning method for the …

The prediction of future drought is an effective mitigation tool for assessing adverse
consequences of drought events on vital water resources, agriculture, ecosystems and …

Large-scale reservoirs play an essential role in water resources management for agriculture
irrigation, water supply and flood controls. However, we need robust reservoir operation …

In this paper, several soft computing approaches were employed for rainfall prediction. Two
aspects were considered to improve the accuracy of rainfall prediction:(1) carrying out a data …

Urban flood control is a crucial task, which commonly faces fast rising peak flows resulting
from urbanization. To mitigate future flood damages, it is imperative to construct an on-line …

In this paper, an effective hybrid optimization strategy by incorporating the adaptive
optimization of particle swarm optimization (PSO) into genetic algorithm (GA), namely …