FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2794103404> ?p ?o ?g. }

• W2794103404 endingPage "526" @default.
• W2794103404 startingPage "526" @default.
• W2794103404 abstract "Wind power generation has presented an important development around the world. However, its integration into electrical systems presents numerous challenges due to the variable nature of the wind. Therefore, to maintain an economical and reliable electricity supply, it is necessary to accurately predict wind generation. The Wind Power Prediction Tool (WPPT) has been proposed to solve this task using the power curve associated with a wind farm. Recurrent Neural Networks (RNNs) model complex non-linear relationships without requiring explicit mathematical expressions that relate the variables involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed, but using LSTM blocks as units in the hidden layer. The training process of this network has two key stages: (i) the hidden layer is trained with a descending gradient method online using one epoch; (ii) the output layer is adjusted with a regularized regression. In particular, the case is proposed where Step (i) is used as a target for the input signal, in order to extract characteristics automatically as the autoencoder approach; and in the second stage (ii), a quantile regression is used in order to obtain a robust estimate of the expected target. The experimental results show that LSTM+ESN using the autoencoder and quantile regression outperforms the WPPT model in all global metrics used." @default.
• W2794103404 created "2018-03-29" @default.
• W2794103404 creator A5030111247 @default.
• W2794103404 creator A5054421707 @default.
• W2794103404 creator A5086543764 @default.
• W2794103404 creator A5087969595 @default.
• W2794103404 date "2018-02-28" @default.
• W2794103404 modified "2023-10-16" @default.
• W2794103404 title "Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory" @default.
• W2794103404 cites W1583817058 @default.
• W2794103404 cites W1984703120 @default.
• W2794103404 cites W1994170512 @default.
• W2794103404 cites W2016589492 @default.
• W2794103404 cites W2024692966 @default.
• W2794103404 cites W2034954612 @default.
• W2794103404 cites W2041155726 @default.
• W2794103404 cites W2048857692 @default.
• W2794103404 cites W2058504886 @default.
• W2794103404 cites W2064675550 @default.
• W2794103404 cites W2067656095 @default.
• W2794103404 cites W2075967464 @default.
• W2794103404 cites W2080267209 @default.
• W2794103404 cites W2087394284 @default.
• W2794103404 cites W2107794886 @default.
• W2794103404 cites W2107878631 @default.
• W2794103404 cites W2141703670 @default.
• W2794103404 cites W2141838814 @default.
• W2794103404 cites W2147107577 @default.
• W2794103404 cites W2150355110 @default.
• W2794103404 cites W2171865010 @default.
• W2794103404 cites W2185918355 @default.
• W2794103404 cites W2189312358 @default.
• W2794103404 cites W2287279778 @default.
• W2794103404 cites W2313458828 @default.
• W2794103404 cites W2346420766 @default.
• W2794103404 cites W2521080030 @default.
• W2794103404 cites W2573587735 @default.
• W2794103404 cites W2734535856 @default.
• W2794103404 cites W2766569626 @default.
• W2794103404 cites W2774931013 @default.
• W2794103404 cites W2775819639 @default.
• W2794103404 doi "https://doi.org/10.3390/en11030526" @default.
• W2794103404 hasPublicationYear "2018" @default.
• W2794103404 type Work @default.
• W2794103404 sameAs 2794103404 @default.
• W2794103404 citedByCount "80" @default.
• W2794103404 countsByYear W27941034042018 @default.
• W2794103404 countsByYear W27941034042019 @default.
• W2794103404 countsByYear W27941034042020 @default.
• W2794103404 countsByYear W27941034042021 @default.
• W2794103404 countsByYear W27941034042022 @default.
• W2794103404 countsByYear W27941034042023 @default.
• W2794103404 crossrefType "journal-article" @default.
• W2794103404 hasAuthorship W2794103404A5030111247 @default.
• W2794103404 hasAuthorship W2794103404A5054421707 @default.
• W2794103404 hasAuthorship W2794103404A5086543764 @default.
• W2794103404 hasAuthorship W2794103404A5087969595 @default.
• W2794103404 hasBestOaLocation W27941034041 @default.
• W2794103404 hasConcept C101738243 @default.
• W2794103404 hasConcept C105795698 @default.
• W2794103404 hasConcept C119599485 @default.
• W2794103404 hasConcept C119857082 @default.
• W2794103404 hasConcept C121332964 @default.
• W2794103404 hasConcept C127413603 @default.
• W2794103404 hasConcept C147168706 @default.
• W2794103404 hasConcept C151406439 @default.
• W2794103404 hasConcept C154945302 @default.
• W2794103404 hasConcept C172025690 @default.
• W2794103404 hasConcept C33923547 @default.
• W2794103404 hasConcept C41008148 @default.
• W2794103404 hasConcept C50644808 @default.
• W2794103404 hasConcept C61797465 @default.
• W2794103404 hasConcept C62520636 @default.
• W2794103404 hasConcept C63817138 @default.
• W2794103404 hasConcept C78600449 @default.
• W2794103404 hasConcept C83546350 @default.
• W2794103404 hasConceptScore W2794103404C101738243 @default.
• W2794103404 hasConceptScore W2794103404C105795698 @default.
• W2794103404 hasConceptScore W2794103404C119599485 @default.
• W2794103404 hasConceptScore W2794103404C119857082 @default.
• W2794103404 hasConceptScore W2794103404C121332964 @default.
• W2794103404 hasConceptScore W2794103404C127413603 @default.
• W2794103404 hasConceptScore W2794103404C147168706 @default.
• W2794103404 hasConceptScore W2794103404C151406439 @default.
• W2794103404 hasConceptScore W2794103404C154945302 @default.
• W2794103404 hasConceptScore W2794103404C172025690 @default.
• W2794103404 hasConceptScore W2794103404C33923547 @default.
• W2794103404 hasConceptScore W2794103404C41008148 @default.
• W2794103404 hasConceptScore W2794103404C50644808 @default.
• W2794103404 hasConceptScore W2794103404C61797465 @default.
• W2794103404 hasConceptScore W2794103404C62520636 @default.
• W2794103404 hasConceptScore W2794103404C63817138 @default.
• W2794103404 hasConceptScore W2794103404C78600449 @default.
• W2794103404 hasConceptScore W2794103404C83546350 @default.
• W2794103404 hasIssue "3" @default.
• W2794103404 hasLocation W27941034041 @default.
• W2794103404 hasLocation W27941034042 @default.
• W2794103404 hasLocation W27941034043 @default.

• next