Hydrological models are vital component and essential tools for water resources and
environmental planning and management. In recent times, several studies have been …

Research on rainfall prediction contributes to different fields that have a huge impact on our
daily life. With the advancement of computer technology, machine learning has been …

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

The prediction method plays crucial roles in accurate precipitation forecasts. Recently,
machine learning has been widely used for forecasting precipitation, and the K-nearest …

Rainfall has a great impact on agriculture and people's daily travel, so accurate prediction of
precipitation is well worth studying for researchers. Traditional methods like numerical …

Rainfall prediction is the active area of research as it enables the farmers to move with the
effective decision-making regarding agriculture in both cultivation and irrigation. The existing …

This study proposes a new hybrid biogeography-based optimization (BBO) technique to
achieve a better balance between exploitation and exploration sides of BBO. The proposed …

Rainfall is crucial for the development and management of water resources. Six hybrid soft
computing models, including multilayer perceptron (MLP)–Henry gas solubility optimization …

This paper reports a high-level python package for selecting machine learning algorithms
and ensembles of machine learning algorithms parameters by using the particle swarm …

Precipitation deficit causes meteorological drought, and its continuation appears as other
different types of droughts including hydrological, agricultural, economic, and social …