Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387378423> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W4387378423 endingPage "121951" @default.
- W4387378423 startingPage "121951" @default.
- W4387378423 abstract "Persistent PM2.5 pollution poses a serious threat to human health. Developing an accurate urban regional PM2.5 forecasting is of practical significance for environmental protection. However, previous studies have mostly focused on individual monitoring stations, neglecting the influence of neighboring stations, which limits forecasting accuracy. Additionally, the PM2.5 of a single monitoring station cannot reflect the overall situation of a region. Therefore, this paper develops a novel PM2.5 spatiotemporal forecasting framework that combines graph convolutional module, temporal convolutional module, linear module. It enables the forecasting of PM2.5 concentrations at multiple stations and multiple time steps in the future. Concretely, we utilize a mixed graph convolutional network extract the spatial features of PM2.5. Then, an improved temporal convolutional network, the second-order residual temporal convolutional network, is developed to capture complex temporal features. Following the classical “linear and non-linear” modeling strategy, a linear module is added to the forecasting framework. Experiments on the real air pollution dataset from Beijing demonstate that our framework outperforms the state-of-the-art baselines." @default.
- W4387378423 created "2023-10-06" @default.
- W4387378423 creator A5004641057 @default.
- W4387378423 creator A5015820030 @default.
- W4387378423 creator A5056185510 @default.
- W4387378423 creator A5067617401 @default.
- W4387378423 date "2024-03-01" @default.
- W4387378423 modified "2023-10-18" @default.
- W4387378423 title "A forecasting framework on fusion of spatiotemporal features for multi-station PM2.5" @default.
- W4387378423 cites W1968840994 @default.
- W4387378423 cites W1977177161 @default.
- W4387378423 cites W1990092328 @default.
- W4387378423 cites W2064675550 @default.
- W4387378423 cites W2111286455 @default.
- W4387378423 cites W2117123725 @default.
- W4387378423 cites W2121690346 @default.
- W4387378423 cites W2129242535 @default.
- W4387378423 cites W2138742333 @default.
- W4387378423 cites W2194775991 @default.
- W4387378423 cites W2573212922 @default.
- W4387378423 cites W2581082906 @default.
- W4387378423 cites W2587362166 @default.
- W4387378423 cites W2740369742 @default.
- W4387378423 cites W2766040222 @default.
- W4387378423 cites W2789849108 @default.
- W4387378423 cites W2803892188 @default.
- W4387378423 cites W2812669263 @default.
- W4387378423 cites W2897897407 @default.
- W4387378423 cites W2901504064 @default.
- W4387378423 cites W2914487400 @default.
- W4387378423 cites W2947156405 @default.
- W4387378423 cites W2965341826 @default.
- W4387378423 cites W2990955039 @default.
- W4387378423 cites W3013755684 @default.
- W4387378423 cites W3080253043 @default.
- W4387378423 cites W3103720336 @default.
- W4387378423 cites W3115103108 @default.
- W4387378423 cites W3123826259 @default.
- W4387378423 cites W3124650867 @default.
- W4387378423 cites W3131600262 @default.
- W4387378423 cites W4200099066 @default.
- W4387378423 cites W4224307186 @default.
- W4387378423 cites W4224947654 @default.
- W4387378423 cites W4294203719 @default.
- W4387378423 doi "https://doi.org/10.1016/j.eswa.2023.121951" @default.
- W4387378423 hasPublicationYear "2024" @default.
- W4387378423 type Work @default.
- W4387378423 citedByCount "0" @default.
- W4387378423 crossrefType "journal-article" @default.
- W4387378423 hasAuthorship W4387378423A5004641057 @default.
- W4387378423 hasAuthorship W4387378423A5015820030 @default.
- W4387378423 hasAuthorship W4387378423A5056185510 @default.
- W4387378423 hasAuthorship W4387378423A5067617401 @default.
- W4387378423 hasConcept C11413529 @default.
- W4387378423 hasConcept C119857082 @default.
- W4387378423 hasConcept C124101348 @default.
- W4387378423 hasConcept C132525143 @default.
- W4387378423 hasConcept C154945302 @default.
- W4387378423 hasConcept C155512373 @default.
- W4387378423 hasConcept C17744445 @default.
- W4387378423 hasConcept C191935318 @default.
- W4387378423 hasConcept C199539241 @default.
- W4387378423 hasConcept C2778304055 @default.
- W4387378423 hasConcept C41008148 @default.
- W4387378423 hasConcept C80444323 @default.
- W4387378423 hasConcept C81363708 @default.
- W4387378423 hasConceptScore W4387378423C11413529 @default.
- W4387378423 hasConceptScore W4387378423C119857082 @default.
- W4387378423 hasConceptScore W4387378423C124101348 @default.
- W4387378423 hasConceptScore W4387378423C132525143 @default.
- W4387378423 hasConceptScore W4387378423C154945302 @default.
- W4387378423 hasConceptScore W4387378423C155512373 @default.
- W4387378423 hasConceptScore W4387378423C17744445 @default.
- W4387378423 hasConceptScore W4387378423C191935318 @default.
- W4387378423 hasConceptScore W4387378423C199539241 @default.
- W4387378423 hasConceptScore W4387378423C2778304055 @default.
- W4387378423 hasConceptScore W4387378423C41008148 @default.
- W4387378423 hasConceptScore W4387378423C80444323 @default.
- W4387378423 hasConceptScore W4387378423C81363708 @default.
- W4387378423 hasLocation W43873784231 @default.
- W4387378423 hasOpenAccess W4387378423 @default.
- W4387378423 hasPrimaryLocation W43873784231 @default.
- W4387378423 hasRelatedWork W2015747722 @default.
- W4387378423 hasRelatedWork W2361035307 @default.
- W4387378423 hasRelatedWork W2362050182 @default.
- W4387378423 hasRelatedWork W2369897927 @default.
- W4387378423 hasRelatedWork W2380455807 @default.
- W4387378423 hasRelatedWork W2382418233 @default.
- W4387378423 hasRelatedWork W2993975634 @default.
- W4387378423 hasRelatedWork W3031731056 @default.
- W4387378423 hasRelatedWork W4293167957 @default.
- W4387378423 hasRelatedWork W4300237897 @default.
- W4387378423 hasVolume "238" @default.
- W4387378423 isParatext "false" @default.
- W4387378423 isRetracted "false" @default.
- W4387378423 workType "article" @default.