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Data Analysis to Generate Models Based on Neural Network and Regression for Solar Power Generation Forecasting

https://doi.org/10.1109/isms.2016.65

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1109/eeeic-2.2013.6737883openalex-snapshot

Generalized neural network methodology for short term solar power forecasting

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Solar radiation modelling for the estimation of the solar energy generation

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Forecasting of photovoltaic power yield using dynamic neural networks

inferredcites →https://doi.org/10.1109/indin.2009.5195808openalex-snapshot

Solar radiation forecasting based on meteorological data using artificial neural networks

inferredcites →https://doi.org/10.1109/isgt.2012.6175757openalex-snapshot

Solar radiation prediction based on recurrent neural networks trained by Levenberg-Marquardt backpropagation learning algorithm

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Solar power probabilistic forecasting by using multiple linear regression analysis

inferredcites →https://doi.org/10.1109/tdc.2012.6281569openalex-snapshot

A data mining method for selecting input variables for forecasting model of global solar radiation

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Short-Term Load Forecasting Using Soft Computing Techniques

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Computational Intelligence in Energy Generation

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