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Air passenger travel forecasting model based on both dynamical individual behavior and social influence force
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| Zeitschriftentitel: | Journal of Algorithms & Computational Technology |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Journal of Algorithms & Computational Technology, 13, 2019, S. 174830261988139 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
SAGE Publications
|
| author_facet |
Wang, Jialiang Liu, Xiaoqing Ding, Jianli Wang, Jialiang Liu, Xiaoqing Ding, Jianli |
|---|---|
| author |
Wang, Jialiang Liu, Xiaoqing Ding, Jianli |
| spellingShingle |
Wang, Jialiang Liu, Xiaoqing Ding, Jianli Journal of Algorithms & Computational Technology Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| author_sort |
wang, jialiang |
| spelling |
Wang, Jialiang Liu, Xiaoqing Ding, Jianli 1748-3026 1748-3026 SAGE Publications http://dx.doi.org/10.1177/1748302619881392 <jats:p> Air passenger travel forecasting is necessary and becomes very valuable for airline company, because accurately obtaining practical requirements of air passenger, which can not only help airline company to improve air passenger satisfaction degree and enhance user experience so as to gain huge revenue, but also can help air passengers discover suitable travel plan quickly. In order to generate the air passenger travel forecasting model, this paper aims to analyze the internal driving force and social affect factor simultaneously, which was based on dynamical personal behaviors and air passenger social relationship exactly. In particular, three aspects in terms of dynamical personal behaviors, effect of fellow air passenger, and influence of similar air passenger are all considered simultaneously, and then the data from these aspects are further trained so as to obtain weight allocation in many different scenarios. Besides, workday and non-workday are separately considered in order to make the forecasting model feasible and effective. </jats:p> Air passenger travel forecasting model based on both dynamical individual behavior and social influence force Journal of Algorithms & Computational Technology |
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| title |
Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_unstemmed |
Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_full |
Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_fullStr |
Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_full_unstemmed |
Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
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Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_sort |
air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
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http://dx.doi.org/10.1177/1748302619881392 |
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2019 |
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<jats:p> Air passenger travel forecasting is necessary and becomes very valuable for airline company, because accurately obtaining practical requirements of air passenger, which can not only help airline company to improve air passenger satisfaction degree and enhance user experience so as to gain huge revenue, but also can help air passengers discover suitable travel plan quickly. In order to generate the air passenger travel forecasting model, this paper aims to analyze the internal driving force and social affect factor simultaneously, which was based on dynamical personal behaviors and air passenger social relationship exactly. In particular, three aspects in terms of dynamical personal behaviors, effect of fellow air passenger, and influence of similar air passenger are all considered simultaneously, and then the data from these aspects are further trained so as to obtain weight allocation in many different scenarios. Besides, workday and non-workday are separately considered in order to make the forecasting model feasible and effective. </jats:p> |
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| author | Wang, Jialiang, Liu, Xiaoqing, Ding, Jianli |
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| description | <jats:p> Air passenger travel forecasting is necessary and becomes very valuable for airline company, because accurately obtaining practical requirements of air passenger, which can not only help airline company to improve air passenger satisfaction degree and enhance user experience so as to gain huge revenue, but also can help air passengers discover suitable travel plan quickly. In order to generate the air passenger travel forecasting model, this paper aims to analyze the internal driving force and social affect factor simultaneously, which was based on dynamical personal behaviors and air passenger social relationship exactly. In particular, three aspects in terms of dynamical personal behaviors, effect of fellow air passenger, and influence of similar air passenger are all considered simultaneously, and then the data from these aspects are further trained so as to obtain weight allocation in many different scenarios. Besides, workday and non-workday are separately considered in order to make the forecasting model feasible and effective. </jats:p> |
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| spelling | Wang, Jialiang Liu, Xiaoqing Ding, Jianli 1748-3026 1748-3026 SAGE Publications http://dx.doi.org/10.1177/1748302619881392 <jats:p> Air passenger travel forecasting is necessary and becomes very valuable for airline company, because accurately obtaining practical requirements of air passenger, which can not only help airline company to improve air passenger satisfaction degree and enhance user experience so as to gain huge revenue, but also can help air passengers discover suitable travel plan quickly. In order to generate the air passenger travel forecasting model, this paper aims to analyze the internal driving force and social affect factor simultaneously, which was based on dynamical personal behaviors and air passenger social relationship exactly. In particular, three aspects in terms of dynamical personal behaviors, effect of fellow air passenger, and influence of similar air passenger are all considered simultaneously, and then the data from these aspects are further trained so as to obtain weight allocation in many different scenarios. Besides, workday and non-workday are separately considered in order to make the forecasting model feasible and effective. </jats:p> Air passenger travel forecasting model based on both dynamical individual behavior and social influence force Journal of Algorithms & Computational Technology |
| spellingShingle | Wang, Jialiang, Liu, Xiaoqing, Ding, Jianli, Journal of Algorithms & Computational Technology, Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_full | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_fullStr | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_full_unstemmed | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_short | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_sort | air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| title_unstemmed | Air passenger travel forecasting model based on both dynamical individual behavior and social influence force |
| url | http://dx.doi.org/10.1177/1748302619881392 |