Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in …
RC Deo, M Şahin - Renewable and Sustainable Energy Reviews, 2017 - Elsevier
Forecasting solar radiation (G) is extremely crucial for engineering applications (eg design
of solar furnaces and energy-efficient buildings, solar concentrators, photovoltaic-systems …
of solar furnaces and energy-efficient buildings, solar concentrators, photovoltaic-systems …
Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: A new …
Global advocacy to mitigate climate change impacts on pristine environments, wildlife,
ecology, and health has led scientists to design technologies that harness solar energy with …
ecology, and health has led scientists to design technologies that harness solar energy with …
A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
RC Deo, X Wen, F Qi - Applied Energy, 2016 - Elsevier
A solar radiation forecasting model can be utilized is a scientific contrivance for investigating
future viability of solar energy potentials. In this paper, a wavelet-coupled support vector …
future viability of solar energy potentials. In this paper, a wavelet-coupled support vector …
[PDF][PDF] High-quality spatial climate data-sets for Australia
DA Jones, W Wang, R Fawcett - Australian Meteorological and …, 2009 - Citeseer
Recent years have seen much of Australia suffer from severe meteorological drought and a
series of climatic extremes (eg Bureau of Meteorology 2008a, 2008b). As a result, water …
series of climatic extremes (eg Bureau of Meteorology 2008a, 2008b). As a result, water …
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
Solar energy is an alternative renewable energy resource that has the potential of cleanly
addressing the increasing demand for electricity in the modern era to overcome future …
addressing the increasing demand for electricity in the modern era to overcome future …
Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition
Soil moisture (SM) is an essential component of the environmental and the agricultural
system. Continuous monitoring and forecasting of soil moisture is a desirable strategy to …
system. Continuous monitoring and forecasting of soil moisture is a desirable strategy to …
A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China
S Jia, W Zhu, A Lű, T Yan - Remote sensing of Environment, 2011 - Elsevier
The availability of precipitation data with high spatial resolution is of fundamental importance
in several applications such as hydrology, meteorology and ecology. At present, there are …
in several applications such as hydrology, meteorology and ecology. At present, there are …
An improved statistical approach to merge satellite rainfall estimates and raingauge data
Deriving high quality daily rainfall estimates are required not only for successful hydrological
modelling but also for its application in ungauged basins. At present, there are two …
modelling but also for its application in ungauged basins. At present, there are two …
Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm
Forecasting streamflow is vital for strategically planning, utilizing and redistributing water
resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated …
resources. In this paper, a wavelet-hybrid artificial neural network (ANN) model integrated …
[HTML][HTML] Variational mode decomposition based random forest model for solar radiation forecasting: new emerging machine learning technology
Forecasting of solar radiation (Radn) can provide an insight vision for the amount of green
and friendly energy sources. Owing to the non-linearity and non-stationarity challenges …
and friendly energy sources. Owing to the non-linearity and non-stationarity challenges …