TY - JOUR
T1 - A decision-making model using machine learning for improving dispatching efficiency in chengdu shuangliu airport
AU - Qian, Yingmiao
AU - Chen, Shuhang
AU - Li, Jianchang
AU - Ren, Qinxin
AU - Zhu, Jinfu
AU - Yuan, Ruijia
AU - Su, Hao
N1 - Funding Information:
This research was supported by the project of Anhui University of Finance and Economics: Research on the influence mechanism of social relations on the integration ability of the construction engineering innovation system and its ability improvement mechanism (project no. ACKYC20044) and Bengbu Social Science Planning Project: Research on the promotion mechanism and countermeasures of urban quality management ability: a case study of Bengbu City (project no. BB20B003).
Publisher Copyright:
© 2020 Yingmiao Qian et al.
PY - 2020
Y1 - 2020
N2 - Due to the increasing number of people traveling by air, the passenger flow at the airport is increasing, and the problem of passenger drop-off and pickup has a huge impact on urban traffic. The difficulty of taking a taxi at the airport is still a hot issue in the society. Aiming at the problem of optimizing the allocation of taxi resource, this paper is based on the cost-benefit analysis method to determine the factors that affect the taxi driver's decision-making. The mathematical methods such as function equation, BP neural network algorithm, and queuing theory were used to establish a complete decision-making model for taxi drivers and an optimization model of dispatching efficiency at the airport. A conclusion has been drawn that the allocation of airport taxi resource should be arranged closely related to drivers' revenue and the layout of airport line.
AB - Due to the increasing number of people traveling by air, the passenger flow at the airport is increasing, and the problem of passenger drop-off and pickup has a huge impact on urban traffic. The difficulty of taking a taxi at the airport is still a hot issue in the society. Aiming at the problem of optimizing the allocation of taxi resource, this paper is based on the cost-benefit analysis method to determine the factors that affect the taxi driver's decision-making. The mathematical methods such as function equation, BP neural network algorithm, and queuing theory were used to establish a complete decision-making model for taxi drivers and an optimization model of dispatching efficiency at the airport. A conclusion has been drawn that the allocation of airport taxi resource should be arranged closely related to drivers' revenue and the layout of airport line.
UR - http://www.scopus.com/inward/record.url?scp=85098601663&partnerID=8YFLogxK
U2 - 10.1155/2020/6626937
DO - 10.1155/2020/6626937
M3 - Article
AN - SCOPUS:85098601663
SN - 1076-2787
VL - 2020
JO - Complexity
JF - Complexity
M1 - 6626937
ER -