Results 51 to 60 of about 448,336 (218)
Predicting wind energy generation with recurrent neural networks [PDF]
, 2018 Decarbonizing the energy supply requires extensive use of renewable generation. Their intermittent nature requires to obtain accurate forecasts of future generation, at short, mid and long term.
Béjar Alonso, Javier +2 more
core +1 more source
Building thermal load prediction through shallow machine learning and deep learning [PDF]
, 2020 Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity.
Hong, T, Piette, MA, Wang, Z
core
Applied Computational Intelligence and Soft Computing, 2018 The versatility of the neural network (NN) technique allows it to be successfully applied in many fields of science and to a great variety of problems.
Vladimir Krasnopolsky +3 more
doaj +1 more source
Systematic diurnal bias of the CMA-MESO model in southern China: Characteristics and correction
Frontiers in Earth Science, 2023 Model error is an important source of numerical weather prediction (NWP) errors. Among model errors, the systematic diurnal bias plays an important role in high-resolution numerical weather prediction models.
Yuxiao Chen +7 more
doaj +1 more source
A high-order conservative collocation scheme and its application to global shallow-water equations [PDF]
Geoscientific Model Development, 2015 In this paper, an efficient and conservative collocation method is proposed and used to develop a global shallow-water model. Being a nodal type high-order scheme, the present method solves the pointwise values of dependent variables as the unknowns ...
C. Chen, X. Li, X. Shen, F. Xiao
doaj +1 more source
Compatible finite element methods for numerical weather prediction [PDF]
, 2014 This article takes the form of a tutorial on the use of a particular class of mixed finite element methods, which can be thought of as the finite element extension of the C-grid staggered finite difference method.
Cotter, C. J., McRae, A. T. T.
core
Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature [PDF]
Geoscientific Model Development, 2014 Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be
T. Chai, R. R. Draxler
doaj +1 more source
Predicting weather changes [PDF]
MOJ Ecology & Environmental Sciences, 2018 Weather changes can be predicted by studing the pressure distribution over a very large surface area on the surface of the Earth. Wind direction and speed can also help in the prediction of the changes that could occur in wether conditions, depending on the surfaces on which these winds track.
openaire +3 more sources
Hydrology, 2021 Warming sea-surface temperatures (SSTs) have implications for the climate-sensitive Caribbean region, including potential impacts on precipitation. SSTs have been shown to influence deep convection and rainfall, thus understanding the impacts of warming ...
Equisha Glenn +5 more
doaj +1 more source