Matches in SemOpenAlex for { <https://semopenalex.org/work/W2969597613> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2969597613 endingPage "23" @default.
- W2969597613 startingPage "12" @default.
- W2969597613 abstract "El Niño-Southern Oscillation (ENSO) phenomenon is the strongest signal in the interannual time scale of global climate, and has a significant impact on the global short-term climate (temperature, precipitation, etc.). Every year, researchers around the world would predict ENSO for the coming year, and have been studied new forecasting methods all the time, including numerical methods, statistical methods and deep learning methods. The existing deep learning methods are only for the ENSO index or single-point meteorological elements forecasting and rarely involve forecasting of specific regions. In this paper, we formulate a deep learning ENSO forecasting model (DLENSO) to predict ENSO through predicting Sea Surface Temperature (SST) in the tropical Pacific region directly. DLENSO is a sequence to sequence model whose encoder and decoder are both multilayered Convolutional Long Short-Term Memory (ConvLSTM), the input and prediction target of DLENSO are both spatiotemporal sequences. We explore the optimal setting of this model by experiments and report the accuracy on Niño3.4 region to confirm the effectiveness of the proposed method. Moreover, it can be concluded that DLENSO is superior to the LSTM model and deterministic forecast model, and almost equivalent to the ensemble-mean forecast model in the medium and long-term (4–12 months ahead) forecast. This model will pave a new way of predicting ENSO using deep learning technology." @default.
- W2969597613 created "2019-08-29" @default.
- W2969597613 creator A5003459479 @default.
- W2969597613 creator A5037950718 @default.
- W2969597613 creator A5058280062 @default.
- W2969597613 creator A5079173505 @default.
- W2969597613 creator A5088242752 @default.
- W2969597613 date "2019-01-01" @default.
- W2969597613 modified "2023-10-17" @default.
- W2969597613 title "DLENSO: A Deep Learning ENSO Forecasting Model" @default.
- W2969597613 cites W1994654959 @default.
- W2969597613 cites W2002415948 @default.
- W2969597613 cites W2015007962 @default.
- W2969597613 cites W2022124898 @default.
- W2969597613 cites W2064675550 @default.
- W2969597613 cites W2072000799 @default.
- W2969597613 cites W2175723489 @default.
- W2969597613 cites W2261059026 @default.
- W2969597613 cites W2273653372 @default.
- W2969597613 cites W2469330584 @default.
- W2969597613 cites W2472616649 @default.
- W2969597613 cites W2586610618 @default.
- W2969597613 cites W2619995677 @default.
- W2969597613 cites W2963547740 @default.
- W2969597613 cites W950853366 @default.
- W2969597613 doi "https://doi.org/10.1007/978-3-030-29911-8_2" @default.
- W2969597613 hasPublicationYear "2019" @default.
- W2969597613 type Work @default.
- W2969597613 sameAs 2969597613 @default.
- W2969597613 citedByCount "8" @default.
- W2969597613 countsByYear W29695976132020 @default.
- W2969597613 countsByYear W29695976132021 @default.
- W2969597613 countsByYear W29695976132022 @default.
- W2969597613 countsByYear W29695976132023 @default.
- W2969597613 crossrefType "book-chapter" @default.
- W2969597613 hasAuthorship W2969597613A5003459479 @default.
- W2969597613 hasAuthorship W2969597613A5037950718 @default.
- W2969597613 hasAuthorship W2969597613A5058280062 @default.
- W2969597613 hasAuthorship W2969597613A5079173505 @default.
- W2969597613 hasAuthorship W2969597613A5088242752 @default.
- W2969597613 hasConcept C101738243 @default.
- W2969597613 hasConcept C107054158 @default.
- W2969597613 hasConcept C108583219 @default.
- W2969597613 hasConcept C119072478 @default.
- W2969597613 hasConcept C119857082 @default.
- W2969597613 hasConcept C127313418 @default.
- W2969597613 hasConcept C134097258 @default.
- W2969597613 hasConcept C140178040 @default.
- W2969597613 hasConcept C153294291 @default.
- W2969597613 hasConcept C154945302 @default.
- W2969597613 hasConcept C170061395 @default.
- W2969597613 hasConcept C205649164 @default.
- W2969597613 hasConcept C2778112365 @default.
- W2969597613 hasConcept C41008148 @default.
- W2969597613 hasConcept C49204034 @default.
- W2969597613 hasConcept C507956050 @default.
- W2969597613 hasConcept C51040755 @default.
- W2969597613 hasConcept C54355233 @default.
- W2969597613 hasConcept C86803240 @default.
- W2969597613 hasConceptScore W2969597613C101738243 @default.
- W2969597613 hasConceptScore W2969597613C107054158 @default.
- W2969597613 hasConceptScore W2969597613C108583219 @default.
- W2969597613 hasConceptScore W2969597613C119072478 @default.
- W2969597613 hasConceptScore W2969597613C119857082 @default.
- W2969597613 hasConceptScore W2969597613C127313418 @default.
- W2969597613 hasConceptScore W2969597613C134097258 @default.
- W2969597613 hasConceptScore W2969597613C140178040 @default.
- W2969597613 hasConceptScore W2969597613C153294291 @default.
- W2969597613 hasConceptScore W2969597613C154945302 @default.
- W2969597613 hasConceptScore W2969597613C170061395 @default.
- W2969597613 hasConceptScore W2969597613C205649164 @default.
- W2969597613 hasConceptScore W2969597613C2778112365 @default.
- W2969597613 hasConceptScore W2969597613C41008148 @default.
- W2969597613 hasConceptScore W2969597613C49204034 @default.
- W2969597613 hasConceptScore W2969597613C507956050 @default.
- W2969597613 hasConceptScore W2969597613C51040755 @default.
- W2969597613 hasConceptScore W2969597613C54355233 @default.
- W2969597613 hasConceptScore W2969597613C86803240 @default.
- W2969597613 hasLocation W29695976131 @default.
- W2969597613 hasOpenAccess W2969597613 @default.
- W2969597613 hasPrimaryLocation W29695976131 @default.
- W2969597613 hasRelatedWork W2028195289 @default.
- W2969597613 hasRelatedWork W2149706533 @default.
- W2969597613 hasRelatedWork W2172462666 @default.
- W2969597613 hasRelatedWork W2185703788 @default.
- W2969597613 hasRelatedWork W2300759000 @default.
- W2969597613 hasRelatedWork W2522347975 @default.
- W2969597613 hasRelatedWork W2897926287 @default.
- W2969597613 hasRelatedWork W3147949854 @default.
- W2969597613 hasRelatedWork W3173359216 @default.
- W2969597613 hasRelatedWork W3196475251 @default.
- W2969597613 isParatext "false" @default.
- W2969597613 isRetracted "false" @default.
- W2969597613 magId "2969597613" @default.
- W2969597613 workType "book-chapter" @default.