Matches in SemOpenAlex for { <https://semopenalex.org/work/W2336713873> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W2336713873 endingPage "531" @default.
- W2336713873 startingPage "516" @default.
- W2336713873 abstract "In this article, a systematic strategy is proposed to identify severe driving events occurrence correlation with time and location. The proposed approach, which is constructed based on batch clustering and real-time clustering techniques, incorporates historical and real-time data to predict the time and location of severe driving events. Batch clustering is implemented with the combination of subtractive clustering and fuzzy c-means clustering to generate clusters representing the initial correlation patterns. Real-time clustering is then developed to create and update real-time correlation patterns on the foundation of the batch clustering using the evolving Gustafson–Kessel like (eGKL) algorithm. In both clustering processes, the correlation of the events within time domain is identified first, and then two different levels of accurate correlations are conducted for the location domain. Real-time data of operating vehicles each equipped with a data acquisition and wireless communication platform are used to validate the proposed strategy. Batch clustering results reveal the severe braking events distribution and concentration at daytime and nighttime. Real-time clustering provides and updates the variation of the correlations/intercorrelation of different regions. Drivers can be notified of the potential severe driving locations through maps showing the driving routes. Through the variation of the correlations, drivers can recognize the events occurrence at different times and locations. The generated time series can be potentially used to develop spatial-time models for regions to model and forecast the events occurrence." @default.
- W2336713873 created "2016-06-24" @default.
- W2336713873 creator A5008167219 @default.
- W2336713873 creator A5024907692 @default.
- W2336713873 creator A5032717864 @default.
- W2336713873 creator A5034063251 @default.
- W2336713873 creator A5083447907 @default.
- W2336713873 date "2016-04-14" @default.
- W2336713873 modified "2023-10-16" @default.
- W2336713873 title "Cluster-based correlation of severe driving events with time and location" @default.
- W2336713873 cites W1594924988 @default.
- W2336713873 cites W1966905324 @default.
- W2336713873 cites W1973041621 @default.
- W2336713873 cites W1988096524 @default.
- W2336713873 cites W1990368529 @default.
- W2336713873 cites W1991370590 @default.
- W2336713873 cites W1992419399 @default.
- W2336713873 cites W1994096159 @default.
- W2336713873 cites W1997334892 @default.
- W2336713873 cites W2021901779 @default.
- W2336713873 cites W2028425419 @default.
- W2336713873 cites W2036458679 @default.
- W2336713873 cites W2070541676 @default.
- W2336713873 cites W2094350745 @default.
- W2336713873 cites W2122064512 @default.
- W2336713873 cites W2140403765 @default.
- W2336713873 cites W2156415214 @default.
- W2336713873 cites W2159919201 @default.
- W2336713873 cites W2161521785 @default.
- W2336713873 cites W2162151748 @default.
- W2336713873 cites W4289255343 @default.
- W2336713873 cites W43637044 @default.
- W2336713873 doi "https://doi.org/10.1080/15472450.2016.1152891" @default.
- W2336713873 hasPublicationYear "2016" @default.
- W2336713873 type Work @default.
- W2336713873 sameAs 2336713873 @default.
- W2336713873 citedByCount "3" @default.
- W2336713873 countsByYear W23367138732019 @default.
- W2336713873 countsByYear W23367138732021 @default.
- W2336713873 countsByYear W23367138732023 @default.
- W2336713873 crossrefType "journal-article" @default.
- W2336713873 hasAuthorship W2336713873A5008167219 @default.
- W2336713873 hasAuthorship W2336713873A5024907692 @default.
- W2336713873 hasAuthorship W2336713873A5032717864 @default.
- W2336713873 hasAuthorship W2336713873A5034063251 @default.
- W2336713873 hasAuthorship W2336713873A5083447907 @default.
- W2336713873 hasConcept C117220453 @default.
- W2336713873 hasConcept C124101348 @default.
- W2336713873 hasConcept C154945302 @default.
- W2336713873 hasConcept C17212007 @default.
- W2336713873 hasConcept C193143536 @default.
- W2336713873 hasConcept C2524010 @default.
- W2336713873 hasConcept C33704608 @default.
- W2336713873 hasConcept C33923547 @default.
- W2336713873 hasConcept C41008148 @default.
- W2336713873 hasConcept C73555534 @default.
- W2336713873 hasConcept C94641424 @default.
- W2336713873 hasConceptScore W2336713873C117220453 @default.
- W2336713873 hasConceptScore W2336713873C124101348 @default.
- W2336713873 hasConceptScore W2336713873C154945302 @default.
- W2336713873 hasConceptScore W2336713873C17212007 @default.
- W2336713873 hasConceptScore W2336713873C193143536 @default.
- W2336713873 hasConceptScore W2336713873C2524010 @default.
- W2336713873 hasConceptScore W2336713873C33704608 @default.
- W2336713873 hasConceptScore W2336713873C33923547 @default.
- W2336713873 hasConceptScore W2336713873C41008148 @default.
- W2336713873 hasConceptScore W2336713873C73555534 @default.
- W2336713873 hasConceptScore W2336713873C94641424 @default.
- W2336713873 hasIssue "6" @default.
- W2336713873 hasLocation W23367138731 @default.
- W2336713873 hasOpenAccess W2336713873 @default.
- W2336713873 hasPrimaryLocation W23367138731 @default.
- W2336713873 hasRelatedWork W2036503911 @default.
- W2336713873 hasRelatedWork W2143402976 @default.
- W2336713873 hasRelatedWork W2165695836 @default.
- W2336713873 hasRelatedWork W2357149509 @default.
- W2336713873 hasRelatedWork W2389934482 @default.
- W2336713873 hasRelatedWork W2970954390 @default.
- W2336713873 hasRelatedWork W3168768270 @default.
- W2336713873 hasRelatedWork W3176177124 @default.
- W2336713873 hasRelatedWork W4241252752 @default.
- W2336713873 hasRelatedWork W2185743328 @default.
- W2336713873 hasVolume "20" @default.
- W2336713873 isParatext "false" @default.
- W2336713873 isRetracted "false" @default.
- W2336713873 magId "2336713873" @default.
- W2336713873 workType "article" @default.