Weather forecasting is the practice of predicting the state of the atmosphere for a given
location based on different weather parameters. Weather forecasts are made by gathering …

In this research, a weather forecasting model based on machine learning is proposed for
improving the accuracy and efficiency of forecasting. The aim of this research is to propose a …

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

In this paper, we investigate mathematical models of meteorological forecasting based on
the work of neural networks, which allow us to calculate presumptive meteorological …

Daily Weather forecasting is used for multiple reasons in multiple areas like agriculture,
energy supply, transportations, etc. Accuracy of weather conditions shown in forecast reports …

In this paper, we introduce the Spectral Coefficient Learning via Operator Network (SCLON),
a novel operator learning-based approach for solving parametric partial differential …

Accurate forecasting of renewable energy resources has a deep societal and environmental
impact. In this work, we investigate the efficacy and applicability of the Window-Sliding …

As a common data-driven method, artificial neural networks have been widely used in
electricity spot price forecasting. To improve the accuracy of short-term forecasts, this paper …

Missing data are integral parts of most real datasets. To provide an efficient and accurate
analytical result of data, the datasets need to be processed using imputation and cleaning …

Impact forecasts and warnings (IFW) are key to resilience for hydrometeorological hazards.
Communicating the potential social, economic, and environmental hazard impacts allows …