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The worldwide increase in the integration of photovoltaic generation has necessitated improvements in the forecasting approaches. Two models are proposed to cater for PV generation forecasts for few minutes to several hours look-ahead times. A very fast and accurate prediction model based on extreme learning machine is deployed for day-ahead prediction. Moreover, an adaptive and sequential model is...
This study proposed a novel HPSO-SVR model that hybridized the particle swarm optimization (PSO) and support vector regression (SVR) to improve the regression accuracy based on the type of kernel function and kernel parameter value optimization with a small and appropriate feature subset, which is then applied to forecast the monthly rainfall. This optimization mechanism combined the discrete PSO...
In order to forecast industrial-waste-emissions much more accurate, a hybrid system to improve the precision of forecasting, which is the BP neural network. At first, we cluster the data of the export products and industrial-waste-emissions in China. And then, the data is used to develop classification rules and trains BP neural network. It was also proved that the model was feasible and easy to use...
With the development of high rate data transmission technology via distribution line communication, the electric power, data, voice and video can be transferred in the same electric power distribution network, and the technology will be put in operation widely in the future. However the traditional technology of power line communication is not adaptable to the complex and harsh environment of distribution...
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