To recognize application of Artificial Neural Networks (ANNs) in weather forecasting,
especially in rainfall forecasting a comprehensive literature review from 1923 to 2012 is …

Nowadays, mathematical models are widely used to predict climate processes, but little has
been done to compare the models. In this study, multiple linear regression (MLR), multi-layer …

Rainfall prediction is one of the most important and challenging task in the modern world. In
general, climate and rainfall are highly non-linear and complicated phenomena, which …

This study develops a late spring-early summer rainfall forecasting model using an artificial
neural network (ANN) for the Geum River Basin in South Korea. After identifying the lagged …

Large-scale annual climate indices were used to forecast annual drought conditions in the
Maharlu-Bakhtegan watershed, located in Iran, using a neuro-fuzzy model. The …

In this paper, a hybrid wavelet neural network (HWNN) model is developed for effectively
forecasting monthly rainfall from antecedent monthly rainfall and climate indices by …

Rainfall hindcasting is one of the most challenging tasks in the hydrometeorological
forecasting community. The current ad hoc data-driven approaches appear to be insufficient …

Climate change has been emerging as one of the major challenges in the global scenario.
Changes in climate may lead to adverse negative impacts on both natural and human …

Large-scale climatic circulation modulates the weather patterns around the world.
Understanding the teleconnections between large-scale circulation and local hydro …

Since 1990s, computational intelligence models have been widely used in several
applications of weather forecasting. Thanks to their ability to have powerful pattern …