FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4296124210> ?p ?o ?g. }

• W4296124210 endingPage "118716" @default.
• W4296124210 startingPage "118716" @default.
• W4296124210 abstract "Vehicle utilization analysis is an essential tool for manufacturers to understand customer needs, improve equipment uptime, and to collect information for future vehicle and service development. Typically today, this behavioral modeling is done on high-resolution time-resolved data with features such as GPS position and fuel consumption. However, high-resolution data is costly to transfer and sensitive from a privacy perspective. Therefore, such data is typically only collected when the customer pays for extra services relying on that data. This motivated us to develop a multi-task ensemble approach to transfer knowledge from the high-resolution data and enable vehicle behavior prediction from low-resolution but high dimensional data that is aggregated over time in the vehicles. This study proposes a multi-task snapshot-stacked ensemble (MTSSE) deep neural network for vehicle behavior prediction by considering vehicles’ low-resolution operational life records. The multi-task ensemble approach utilizes the measurements to map the low-frequency vehicle usage to the vehicle behaviors defined from the high-resolution time-resolved data. Two data sources are integrated and used: high-resolution data called Dynafleet, and low-resolution so-called Logged Vehicle Data (LVD). The experimental results demonstrate the proposed approach’s effectiveness in predicting the vehicle behavior from low frequency data. With the suggested multi-task snapshot-stacked ensemble deep network, it is shown how low-resolution sensor data can highly contribute to predicting multiple vehicle behaviors simultaneously while using only one single training process." @default.
• W4296124210 created "2022-09-17" @default.
• W4296124210 creator A5003233304 @default.
• W4296124210 creator A5019978147 @default.
• W4296124210 creator A5022044150 @default.
• W4296124210 creator A5076881250 @default.
• W4296124210 creator A5078557032 @default.
• W4296124210 date "2023-02-01" @default.
• W4296124210 modified "2023-10-18" @default.
• W4296124210 title "Predicting Vehicle Behavior Using Multi-task Ensemble Learning" @default.
• W4296124210 cites W1677182931 @default.
• W4296124210 cites W2011369927 @default.
• W4296124210 cites W2140466491 @default.
• W4296124210 cites W2547705281 @default.
• W4296124210 cites W2557748900 @default.
• W4296124210 cites W2565658647 @default.
• W4296124210 cites W2745090846 @default.
• W4296124210 cites W2776641310 @default.
• W4296124210 cites W2790882261 @default.
• W4296124210 cites W2943868962 @default.
• W4296124210 cites W2970602317 @default.
• W4296124210 cites W3001866431 @default.
• W4296124210 cites W3003864893 @default.
• W4296124210 cites W3022893663 @default.
• W4296124210 cites W3044867970 @default.
• W4296124210 cites W3047375952 @default.
• W4296124210 cites W3097253724 @default.
• W4296124210 cites W3103312084 @default.
• W4296124210 cites W3111445687 @default.
• W4296124210 cites W3113400305 @default.
• W4296124210 cites W3116476902 @default.
• W4296124210 cites W3136504339 @default.
• W4296124210 cites W3152949549 @default.
• W4296124210 cites W3201765390 @default.
• W4296124210 cites W4200497959 @default.
• W4296124210 cites W4205325124 @default.
• W4296124210 cites W4206936436 @default.
• W4296124210 cites W4220957759 @default.
• W4296124210 doi "https://doi.org/10.1016/j.eswa.2022.118716" @default.
• W4296124210 hasPublicationYear "2023" @default.
• W4296124210 type Work @default.
• W4296124210 citedByCount "2" @default.
• W4296124210 countsByYear W42961242102023 @default.
• W4296124210 crossrefType "journal-article" @default.
• W4296124210 hasAuthorship W4296124210A5003233304 @default.
• W4296124210 hasAuthorship W4296124210A5019978147 @default.
• W4296124210 hasAuthorship W4296124210A5022044150 @default.
• W4296124210 hasAuthorship W4296124210A5076881250 @default.
• W4296124210 hasAuthorship W4296124210A5078557032 @default.
• W4296124210 hasBestOaLocation W42961242101 @default.
• W4296124210 hasConcept C108583219 @default.
• W4296124210 hasConcept C119857082 @default.
• W4296124210 hasConcept C124101348 @default.
• W4296124210 hasConcept C127413603 @default.
• W4296124210 hasConcept C150899416 @default.
• W4296124210 hasConcept C154945302 @default.
• W4296124210 hasConcept C201995342 @default.
• W4296124210 hasConcept C2780451532 @default.
• W4296124210 hasConcept C41008148 @default.
• W4296124210 hasConcept C45942800 @default.
• W4296124210 hasConcept C50644808 @default.
• W4296124210 hasConcept C55282118 @default.
• W4296124210 hasConcept C60229501 @default.
• W4296124210 hasConcept C75684735 @default.
• W4296124210 hasConcept C76155785 @default.
• W4296124210 hasConcept C77088390 @default.
• W4296124210 hasConcept C79403827 @default.
• W4296124210 hasConceptScore W4296124210C108583219 @default.
• W4296124210 hasConceptScore W4296124210C119857082 @default.
• W4296124210 hasConceptScore W4296124210C124101348 @default.
• W4296124210 hasConceptScore W4296124210C127413603 @default.
• W4296124210 hasConceptScore W4296124210C150899416 @default.
• W4296124210 hasConceptScore W4296124210C154945302 @default.
• W4296124210 hasConceptScore W4296124210C201995342 @default.
• W4296124210 hasConceptScore W4296124210C2780451532 @default.
• W4296124210 hasConceptScore W4296124210C41008148 @default.
• W4296124210 hasConceptScore W4296124210C45942800 @default.
• W4296124210 hasConceptScore W4296124210C50644808 @default.
• W4296124210 hasConceptScore W4296124210C55282118 @default.
• W4296124210 hasConceptScore W4296124210C60229501 @default.
• W4296124210 hasConceptScore W4296124210C75684735 @default.
• W4296124210 hasConceptScore W4296124210C76155785 @default.
• W4296124210 hasConceptScore W4296124210C77088390 @default.
• W4296124210 hasConceptScore W4296124210C79403827 @default.
• W4296124210 hasLocation W42961242101 @default.
• W4296124210 hasLocation W42961242102 @default.
• W4296124210 hasLocation W42961242103 @default.
• W4296124210 hasOpenAccess W4296124210 @default.
• W4296124210 hasPrimaryLocation W42961242101 @default.
• W4296124210 hasRelatedWork W2810053714 @default.
• W4296124210 hasRelatedWork W2960456850 @default.
• W4296124210 hasRelatedWork W3014300295 @default.
• W4296124210 hasRelatedWork W3136979370 @default.
• W4296124210 hasRelatedWork W4292874285 @default.
• W4296124210 hasRelatedWork W4293812307 @default.
• W4296124210 hasRelatedWork W4312200629 @default.
• W4296124210 hasRelatedWork W4317565044 @default.
• W4296124210 hasRelatedWork W4382286161 @default.

• next