Matches in SemOpenAlex for { <https://semopenalex.org/work/W3188272681> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W3188272681 abstract "This paper evaluates the performance of several machine learning algorithms for short-term wind speed forecasting. The algorithms evaluated include: Long Short-Term Memory, Extra-Tree, Gradient Boosting Tree, Extreme Gradient Boosting Tree, Voting Averaged, Multi-layer Perceptron, K-Nearest Neighbors, and Support Vector Machine. The performance of the algorithms was evaluated with different error metrics using real wind speed and meteorological data collected from the city of Maceio, Brazil. First, pre-processing methods are applied in the large database to deal with outliers, noisy and missing values. Then, variable selection technique is employed to select the most significant set of variables and their lag-values as input to the forecast algorithm. Results show Voting Averaged algorithm performs better for all forecast time horizons considered, which are 1 hour, 2 hours and 3 hours ahead." @default.
- W3188272681 created "2021-08-16" @default.
- W3188272681 creator A5022523661 @default.
- W3188272681 creator A5033336315 @default.
- W3188272681 creator A5047066285 @default.
- W3188272681 date "2021-06-28" @default.
- W3188272681 modified "2023-09-27" @default.
- W3188272681 title "Short-term Wind Speed Forecasting using Machine Learning Algorithms" @default.
- W3188272681 cites W1808258884 @default.
- W3188272681 cites W2039306928 @default.
- W3188272681 cites W2056132907 @default.
- W3188272681 cites W2522747841 @default.
- W3188272681 cites W2887747362 @default.
- W3188272681 cites W2908011629 @default.
- W3188272681 cites W2936236242 @default.
- W3188272681 cites W2947870382 @default.
- W3188272681 cites W3024790739 @default.
- W3188272681 cites W3088961167 @default.
- W3188272681 doi "https://doi.org/10.1109/powertech46648.2021.9494848" @default.
- W3188272681 hasPublicationYear "2021" @default.
- W3188272681 type Work @default.
- W3188272681 sameAs 3188272681 @default.
- W3188272681 citedByCount "0" @default.
- W3188272681 crossrefType "proceedings-article" @default.
- W3188272681 hasAuthorship W3188272681A5022523661 @default.
- W3188272681 hasAuthorship W3188272681A5033336315 @default.
- W3188272681 hasAuthorship W3188272681A5047066285 @default.
- W3188272681 hasConcept C11413529 @default.
- W3188272681 hasConcept C119857082 @default.
- W3188272681 hasConcept C121332964 @default.
- W3188272681 hasConcept C12267149 @default.
- W3188272681 hasConcept C124101348 @default.
- W3188272681 hasConcept C153294291 @default.
- W3188272681 hasConcept C154945302 @default.
- W3188272681 hasConcept C161067210 @default.
- W3188272681 hasConcept C169258074 @default.
- W3188272681 hasConcept C41008148 @default.
- W3188272681 hasConcept C46686674 @default.
- W3188272681 hasConcept C50644808 @default.
- W3188272681 hasConcept C60908668 @default.
- W3188272681 hasConcept C61797465 @default.
- W3188272681 hasConcept C62520636 @default.
- W3188272681 hasConcept C70153297 @default.
- W3188272681 hasConcept C79337645 @default.
- W3188272681 hasConceptScore W3188272681C11413529 @default.
- W3188272681 hasConceptScore W3188272681C119857082 @default.
- W3188272681 hasConceptScore W3188272681C121332964 @default.
- W3188272681 hasConceptScore W3188272681C12267149 @default.
- W3188272681 hasConceptScore W3188272681C124101348 @default.
- W3188272681 hasConceptScore W3188272681C153294291 @default.
- W3188272681 hasConceptScore W3188272681C154945302 @default.
- W3188272681 hasConceptScore W3188272681C161067210 @default.
- W3188272681 hasConceptScore W3188272681C169258074 @default.
- W3188272681 hasConceptScore W3188272681C41008148 @default.
- W3188272681 hasConceptScore W3188272681C46686674 @default.
- W3188272681 hasConceptScore W3188272681C50644808 @default.
- W3188272681 hasConceptScore W3188272681C60908668 @default.
- W3188272681 hasConceptScore W3188272681C61797465 @default.
- W3188272681 hasConceptScore W3188272681C62520636 @default.
- W3188272681 hasConceptScore W3188272681C70153297 @default.
- W3188272681 hasConceptScore W3188272681C79337645 @default.
- W3188272681 hasLocation W31882726811 @default.
- W3188272681 hasOpenAccess W3188272681 @default.
- W3188272681 hasPrimaryLocation W31882726811 @default.
- W3188272681 hasRelatedWork W2979979539 @default.
- W3188272681 hasRelatedWork W3159988495 @default.
- W3188272681 hasRelatedWork W3195168932 @default.
- W3188272681 hasRelatedWork W3204641204 @default.
- W3188272681 hasRelatedWork W4288057626 @default.
- W3188272681 hasRelatedWork W4292373754 @default.
- W3188272681 hasRelatedWork W4293069612 @default.
- W3188272681 hasRelatedWork W4304142064 @default.
- W3188272681 hasRelatedWork W4308191010 @default.
- W3188272681 hasRelatedWork W4361795583 @default.
- W3188272681 isParatext "false" @default.
- W3188272681 isRetracted "false" @default.
- W3188272681 magId "3188272681" @default.
- W3188272681 workType "article" @default.