FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386344172> ?p ?o ?g. }

• W4386344172 endingPage "107034" @default.
• W4386344172 startingPage "107034" @default.
• W4386344172 abstract "An improvement in wind speed prediction is highly necessary for estimating the accuracy as well as stability of wind power. In this work, we proposed probabilistic forecasts of wind speed for predicting the short-term wind speed intervals. The optimal model has been designed by considering three different modules such as data decomposition, prediction, and optimization. Variational-Mode-Decomposition (VMD) is utilized for decomposing the primary time series data into a suitable number of modes followed by the Deep Belief Network (DBN) for probabilistic wind sped prediction. Here the Gauss-Bernoulli restricted Boltzmann machine (GBRBM) and Bernoulli-Bernoulli RBM (BBRBM) are combined in the DBN where the GBRBM is utilized as the initial RBM to convert the continuity feature of the source data into a binomial distribution feature. Multi-kernel-random-vector-functional-link-network (MKRVFLN) is employed here as supervised learning in DBN to avoid long execution time and get the model into local optima. In the model optimization, a hybrid multi-objective Sine-Cosine particle-swarm-optimization (MOSCPSO)is used to optimize the DBN parameters for obtaining high accuracy and strong stability output simultaneously. It determines the wind speed at 95%, 90%, 85%, and 80% prediction interval nominal confidence (PINC). To validate the proposed model and comparing with other benchmark prediction techniques, the data are taken from the wind farm located at Sotavento, Spain, at different time horizons (30 min–1 h) in different seasons. The results obtained demonstrate that the proposed technique outperforms the further existing model on the basis of prediction accuracy and stability." @default.
• W4386344172 created "2023-09-01" @default.
• W4386344172 creator A5012566414 @default.
• W4386344172 creator A5025078574 @default.
• W4386344172 creator A5054611665 @default.
• W4386344172 date "2023-11-01" @default.
• W4386344172 modified "2023-09-27" @default.
• W4386344172 title "Probabilistic prediction of wind speed using an integrated deep belief network optimized by a hybrid multi-objective particle swarm algorithm" @default.
• W4386344172 cites W1495476169 @default.
• W4386344172 cites W1963568649 @default.
• W4386344172 cites W1966499742 @default.
• W4386344172 cites W2008709824 @default.
• W4386344172 cites W2030132134 @default.
• W4386344172 cites W2051086873 @default.
• W4386344172 cites W2058504886 @default.
• W4386344172 cites W2093263590 @default.
• W4386344172 cites W2101057038 @default.
• W4386344172 cites W2102836090 @default.
• W4386344172 cites W2114471530 @default.
• W4386344172 cites W2116064496 @default.
• W4386344172 cites W2126105956 @default.
• W4386344172 cites W2132477882 @default.
• W4386344172 cites W2136922672 @default.
• W4386344172 cites W2144830515 @default.
• W4386344172 cites W2175389419 @default.
• W4386344172 cites W2232317135 @default.
• W4386344172 cites W2392689491 @default.
• W4386344172 cites W2484938157 @default.
• W4386344172 cites W2511683089 @default.
• W4386344172 cites W2543580944 @default.
• W4386344172 cites W2578100862 @default.
• W4386344172 cites W2592540809 @default.
• W4386344172 cites W2737643782 @default.
• W4386344172 cites W2766047633 @default.
• W4386344172 cites W2775425027 @default.
• W4386344172 cites W2783204403 @default.
• W4386344172 cites W2789477383 @default.
• W4386344172 cites W2883694838 @default.
• W4386344172 cites W2955242166 @default.
• W4386344172 cites W2965492561 @default.
• W4386344172 cites W3005001477 @default.
• W4386344172 cites W3014565011 @default.
• W4386344172 cites W3024620312 @default.
• W4386344172 cites W3046194311 @default.
• W4386344172 cites W3094915885 @default.
• W4386344172 cites W3099842405 @default.
• W4386344172 cites W3141258397 @default.
• W4386344172 cites W3159163469 @default.
• W4386344172 cites W3174247950 @default.
• W4386344172 cites W3206985962 @default.
• W4386344172 cites W3215621098 @default.
• W4386344172 cites W3216438535 @default.
• W4386344172 cites W4200372662 @default.
• W4386344172 cites W4229031111 @default.
• W4386344172 cites W4289527244 @default.
• W4386344172 cites W4313472418 @default.
• W4386344172 cites W4313839703 @default.
• W4386344172 cites W4365511087 @default.
• W4386344172 cites W602833636 @default.
• W4386344172 doi "https://doi.org/10.1016/j.engappai.2023.107034" @default.
• W4386344172 hasPublicationYear "2023" @default.
• W4386344172 type Work @default.
• W4386344172 citedByCount "0" @default.
• W4386344172 crossrefType "journal-article" @default.
• W4386344172 hasAuthorship W4386344172A5012566414 @default.
• W4386344172 hasAuthorship W4386344172A5025078574 @default.
• W4386344172 hasAuthorship W4386344172A5054611665 @default.
• W4386344172 hasConcept C112972136 @default.
• W4386344172 hasConcept C11413529 @default.
• W4386344172 hasConcept C119857082 @default.
• W4386344172 hasConcept C121332964 @default.
• W4386344172 hasConcept C12267149 @default.
• W4386344172 hasConcept C153294291 @default.
• W4386344172 hasConcept C154945302 @default.
• W4386344172 hasConcept C161067210 @default.
• W4386344172 hasConcept C41008148 @default.
• W4386344172 hasConcept C49937458 @default.
• W4386344172 hasConcept C50644808 @default.
• W4386344172 hasConcept C85617194 @default.
• W4386344172 hasConcept C97385483 @default.
• W4386344172 hasConceptScore W4386344172C112972136 @default.
• W4386344172 hasConceptScore W4386344172C11413529 @default.
• W4386344172 hasConceptScore W4386344172C119857082 @default.
• W4386344172 hasConceptScore W4386344172C121332964 @default.
• W4386344172 hasConceptScore W4386344172C12267149 @default.
• W4386344172 hasConceptScore W4386344172C153294291 @default.
• W4386344172 hasConceptScore W4386344172C154945302 @default.
• W4386344172 hasConceptScore W4386344172C161067210 @default.
• W4386344172 hasConceptScore W4386344172C41008148 @default.
• W4386344172 hasConceptScore W4386344172C49937458 @default.
• W4386344172 hasConceptScore W4386344172C50644808 @default.
• W4386344172 hasConceptScore W4386344172C85617194 @default.
• W4386344172 hasConceptScore W4386344172C97385483 @default.
• W4386344172 hasLocation W43863441721 @default.
• W4386344172 hasOpenAccess W4386344172 @default.
• W4386344172 hasPrimaryLocation W43863441721 @default.
• W4386344172 hasRelatedWork W1992688197 @default.
• W4386344172 hasRelatedWork W2038479138 @default.

• next