Matches in SemOpenAlex for { <https://semopenalex.org/work/W2894714913> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2894714913 endingPage "2943" @default.
- W2894714913 startingPage "2933" @default.
- W2894714913 abstract "In reality, readings of sensors on highways are usually missing at various unexpected moments due to some sensor or communication errors. These missing values do not only influence the real-time traffic monitoring but also prevent further traffic data mining. In this paper, we propose a multi-view learning method to estimate the missing values for traffic-related time series data. The model combines data-driven algorithms (long-short term memory and support vector regression) and collaborative filtering techniques. It can consider the local and global variation in temporal and spatial views to capture more information from the existing data. The estimations of missing values from four views are aggregated to obtain a final value with a kernel function. Data from a highway network are used to evaluate the performance of the proposed model in terms of accuracy, precision, and agreement. The results indicate that our proposed model outperforms other baselines, especially for block missing pattern with a high missing ratio. Furthermore, the sensitivity of the parameters is analyzed. We can conclude that combining different views can improve the performance of the imputation." @default.
- W2894714913 created "2018-10-12" @default.
- W2894714913 creator A5011769740 @default.
- W2894714913 creator A5012912592 @default.
- W2894714913 creator A5060394098 @default.
- W2894714913 creator A5088095471 @default.
- W2894714913 date "2019-08-01" @default.
- W2894714913 modified "2023-10-11" @default.
- W2894714913 title "Missing Value Imputation for Traffic-Related Time Series Data Based on a Multi-View Learning Method" @default.
- W2894714913 cites W1798398164 @default.
- W2894714913 cites W1971757341 @default.
- W2894714913 cites W1979646154 @default.
- W2894714913 cites W1981982250 @default.
- W2894714913 cites W2004353783 @default.
- W2894714913 cites W2005248249 @default.
- W2894714913 cites W2011925575 @default.
- W2894714913 cites W2017917631 @default.
- W2894714913 cites W2019191255 @default.
- W2894714913 cites W2020641160 @default.
- W2894714913 cites W2031069824 @default.
- W2894714913 cites W2033291788 @default.
- W2894714913 cites W2039015671 @default.
- W2894714913 cites W2039417141 @default.
- W2894714913 cites W2045593919 @default.
- W2894714913 cites W2047627251 @default.
- W2894714913 cites W2049500727 @default.
- W2894714913 cites W2051299429 @default.
- W2894714913 cites W2064675550 @default.
- W2894714913 cites W2078994812 @default.
- W2894714913 cites W2100235918 @default.
- W2894714913 cites W2163150789 @default.
- W2894714913 cites W2179076887 @default.
- W2894714913 cites W2190353863 @default.
- W2894714913 cites W2334686861 @default.
- W2894714913 cites W2342643507 @default.
- W2894714913 cites W2343462218 @default.
- W2894714913 cites W2465297350 @default.
- W2894714913 cites W2528179341 @default.
- W2894714913 cites W2529827714 @default.
- W2894714913 cites W2547812180 @default.
- W2894714913 cites W2583110309 @default.
- W2894714913 cites W2768134894 @default.
- W2894714913 cites W4241115065 @default.
- W2894714913 cites W791265519 @default.
- W2894714913 doi "https://doi.org/10.1109/tits.2018.2869768" @default.
- W2894714913 hasPublicationYear "2019" @default.
- W2894714913 type Work @default.
- W2894714913 sameAs 2894714913 @default.
- W2894714913 citedByCount "105" @default.
- W2894714913 countsByYear W28947149132019 @default.
- W2894714913 countsByYear W28947149132020 @default.
- W2894714913 countsByYear W28947149132021 @default.
- W2894714913 countsByYear W28947149132022 @default.
- W2894714913 countsByYear W28947149132023 @default.
- W2894714913 crossrefType "journal-article" @default.
- W2894714913 hasAuthorship W2894714913A5011769740 @default.
- W2894714913 hasAuthorship W2894714913A5012912592 @default.
- W2894714913 hasAuthorship W2894714913A5060394098 @default.
- W2894714913 hasAuthorship W2894714913A5088095471 @default.
- W2894714913 hasConcept C119857082 @default.
- W2894714913 hasConcept C12267149 @default.
- W2894714913 hasConcept C124101348 @default.
- W2894714913 hasConcept C151406439 @default.
- W2894714913 hasConcept C154945302 @default.
- W2894714913 hasConcept C41008148 @default.
- W2894714913 hasConcept C58041806 @default.
- W2894714913 hasConcept C9357733 @default.
- W2894714913 hasConceptScore W2894714913C119857082 @default.
- W2894714913 hasConceptScore W2894714913C12267149 @default.
- W2894714913 hasConceptScore W2894714913C124101348 @default.
- W2894714913 hasConceptScore W2894714913C151406439 @default.
- W2894714913 hasConceptScore W2894714913C154945302 @default.
- W2894714913 hasConceptScore W2894714913C41008148 @default.
- W2894714913 hasConceptScore W2894714913C58041806 @default.
- W2894714913 hasConceptScore W2894714913C9357733 @default.
- W2894714913 hasIssue "8" @default.
- W2894714913 hasLocation W28947149131 @default.
- W2894714913 hasOpenAccess W2894714913 @default.
- W2894714913 hasPrimaryLocation W28947149131 @default.
- W2894714913 hasRelatedWork W1574575415 @default.
- W2894714913 hasRelatedWork W2024529227 @default.
- W2894714913 hasRelatedWork W2081476516 @default.
- W2894714913 hasRelatedWork W2181530120 @default.
- W2894714913 hasRelatedWork W2581984549 @default.
- W2894714913 hasRelatedWork W3028371478 @default.
- W2894714913 hasRelatedWork W3144172081 @default.
- W2894714913 hasRelatedWork W3179858851 @default.
- W2894714913 hasRelatedWork W4211215373 @default.
- W2894714913 hasRelatedWork W3123177881 @default.
- W2894714913 hasVolume "20" @default.
- W2894714913 isParatext "false" @default.
- W2894714913 isRetracted "false" @default.
- W2894714913 magId "2894714913" @default.
- W2894714913 workType "article" @default.