It is well-known that numerical weather prediction (NWP) models require considerable
computer power to solve complex mathematical equations to obtain a forecast based on …

The main function of an optimizer is to determine in what measure to change the weights
and the learning rate of the neural network to reduce losses. One of the best known …

Weather prediction and meteorological analysis contribute significantly towards sustainable
development to reduce the damage from extreme events which could otherwise set-back the …

Reanalysis wind fields are obtained by correcting the numerically forecasted wind fields
based on observation data (ie, either remote sensing or in-situ observations, or both) …

Soil temperature plays an important role in agriculture, industry and other fields. Accurate
soil temperature prediction can help improve productivity and avoid risks in many fields. At …

Using artificial intelligence to anticipate weather conditions, according to prior research, can
provide positive results. Forecasts of meteorological time series can aid disaster-prevention …

Soil temperature (ST) plays an important role in agriculture and other fields, and has a close
relationship with plant growth and development. Therefore, accurate ST prediction methods …

This paper describes the modeling approach for lower atmosphere dynamics in a selected
location. The purpose of this model is to provide short-term and long-term forecasts of the …

Weather prediction is a challenging research problem although the revolutionary
advancement in deep learning, along with the availability of big data, has significantly …

Among all hydrometeorological parameters, rainfall strongly correlates with
hydrometeorological disasters. The rainfall forecast process remains challenging due to the …