FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4206282046> ?p ?o ?g. }

• W4206282046 endingPage "276" @default.
• W4206282046 startingPage "270" @default.
• W4206282046 abstract "Rental bikes are popular in many urban areas to help people expand their mobility. It is important to make the rental bicycle usable and available to the general public at the appropriate time and place. Inevitably, providing the city with a steady supply of rental bicycles becomes a major concern. The most important aspect is the estimation of the number of bicycles required in each bicycle sharing station at any given hour. This paper gives an examination of human mobility as indicated by bicycle renting information of the bike sharing system. In this paper, we proposed a new approach for forecasting the bike inflow and outflow from one station to another during certain time slots. Our method analyses human mobility pattern by two steps: (1) Using Tuckers tensor decomposition to create a 3D tensor to model human mobility and extract latent temporal and spatial characteristics of various stations and time slots. (2) to use a Long-Short Term Memory Neural Network to model the relationship between mobility patterns and the derived latent spatial and temporal features in order to predict bike flow between stations. The main contribution of this study that with the extracted latent characteristics through Tucker’s factorization we improve the accuracy of prediction by 16% and decrease the amount of training data that used in prediction. Also, a root mean squared error of prediction is 1,5 bikes. We compare our model with baseline models as historical average, ARMA, the feed-forward neural network, and KNN. The proposed method showed the best results" @default.
• W4206282046 created "2022-01-26" @default.
• W4206282046 creator A5006002568 @default.
• W4206282046 creator A5052545560 @default.
• W4206282046 creator A5073854941 @default.
• W4206282046 creator A5084158767 @default.
• W4206282046 date "2021-01-01" @default.
• W4206282046 modified "2023-10-17" @default.
• W4206282046 title "A Prediction of Bike Flow in Bike Renting Systems with the Tensor Model and Deep Learning" @default.
• W4206282046 cites W2004353783 @default.
• W4206282046 cites W2024165284 @default.
• W4206282046 cites W2032251915 @default.
• W4206282046 cites W2053109393 @default.
• W4206282046 cites W2117989646 @default.
• W4206282046 cites W2553435998 @default.
• W4206282046 cites W2593182953 @default.
• W4206282046 cites W2624190409 @default.
• W4206282046 cites W2760534564 @default.
• W4206282046 cites W2771816418 @default.
• W4206282046 cites W2912985636 @default.
• W4206282046 cites W2943827744 @default.
• W4206282046 cites W3005021926 @default.
• W4206282046 cites W3042918615 @default.
• W4206282046 cites W3047066545 @default.
• W4206282046 cites W3103829738 @default.
• W4206282046 doi "https://doi.org/10.1016/j.trpro.2021.11.037" @default.
• W4206282046 hasPublicationYear "2021" @default.
• W4206282046 type Work @default.
• W4206282046 citedByCount "1" @default.
• W4206282046 countsByYear W42062820462023 @default.
• W4206282046 crossrefType "journal-article" @default.
• W4206282046 hasAuthorship W4206282046A5006002568 @default.
• W4206282046 hasAuthorship W4206282046A5052545560 @default.
• W4206282046 hasAuthorship W4206282046A5073854941 @default.
• W4206282046 hasAuthorship W4206282046A5084158767 @default.
• W4206282046 hasBestOaLocation W42062820461 @default.
• W4206282046 hasConcept C119857082 @default.
• W4206282046 hasConcept C124101348 @default.
• W4206282046 hasConcept C127413603 @default.
• W4206282046 hasConcept C147176958 @default.
• W4206282046 hasConcept C154945302 @default.
• W4206282046 hasConcept C22212356 @default.
• W4206282046 hasConcept C2994001137 @default.
• W4206282046 hasConcept C41008148 @default.
• W4206282046 hasConcept C539828613 @default.
• W4206282046 hasConcept C85502023 @default.
• W4206282046 hasConceptScore W4206282046C119857082 @default.
• W4206282046 hasConceptScore W4206282046C124101348 @default.
• W4206282046 hasConceptScore W4206282046C127413603 @default.
• W4206282046 hasConceptScore W4206282046C147176958 @default.
• W4206282046 hasConceptScore W4206282046C154945302 @default.
• W4206282046 hasConceptScore W4206282046C22212356 @default.
• W4206282046 hasConceptScore W4206282046C2994001137 @default.
• W4206282046 hasConceptScore W4206282046C41008148 @default.
• W4206282046 hasConceptScore W4206282046C539828613 @default.
• W4206282046 hasConceptScore W4206282046C85502023 @default.
• W4206282046 hasFunder F4320322726 @default.
• W4206282046 hasLocation W42062820461 @default.
• W4206282046 hasLocation W42062820462 @default.
• W4206282046 hasOpenAccess W4206282046 @default.
• W4206282046 hasPrimaryLocation W42062820461 @default.
• W4206282046 hasRelatedWork W2734603556 @default.
• W4206282046 hasRelatedWork W2961085424 @default.
• W4206282046 hasRelatedWork W3046775127 @default.
• W4206282046 hasRelatedWork W3123088513 @default.
• W4206282046 hasRelatedWork W4285260836 @default.
• W4206282046 hasRelatedWork W4286629047 @default.
• W4206282046 hasRelatedWork W4306321456 @default.
• W4206282046 hasRelatedWork W4306674287 @default.
• W4206282046 hasRelatedWork W4380759248 @default.
• W4206282046 hasRelatedWork W4224009465 @default.
• W4206282046 hasVolume "58" @default.
• W4206282046 isParatext "false" @default.
• W4206282046 isRetracted "false" @default.
• W4206282046 workType "article" @default.