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Start Over Creator Snášel , Václav

2. Supervised learning of photovoltaic power plant output prediction models

Creator:
Prokop, Lukáš, Mišák, Stanislav, Snášel , Václav, Platoš, Jan, and Krömer, Pavel
Format:
bez média and svazek
Type:
model:article and TEXT
Subject:
Supervised learning, fuzzy rules, regression, artificial neural networks, and support vector machines
Language:
English
Description:
This article presents an application of evolutionary fuzzy rules to the modeling and prediction of power output of a real-world Photovoltaic Power Plant (PVPP). The method is compared to artificial neural networks and support vector regression that were also used to build predictors in order to analyse a time-series like data describing the production of the PVPP. The models of the PVPP are created using different supervised machine learning methods in order to forecast the short-term output of the power plant and compare the accuracy of the prediction.
Rights:
http://creativecommons.org/publicdomain/mark/1.0/ and policy:public