|Table of Contents|

[1] Hu Qizhou, Deng Wei, Tan Minjia, Bian Lishuang, et al. Projection pursuit model of vehicle emission on air pollutionat intersections based on the improved bat algorithm [J]. Journal of Southeast University (English Edition), 2019, 35 (3): 389-392. [doi:10.3969/j.issn.1003-7985.2019.03.016]
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Projection pursuit model of vehicle emission on air pollutionat intersections based on the improved bat algorithm()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
35
Issue:
2019 3
Page:
389-392
Research Field:
Computer Science and Engineering
Publishing date:
2019-09-30

Info

Title:
Projection pursuit model of vehicle emission on air pollutionat intersections based on the improved bat algorithm
Author(s):
Hu Qizhou1;  Deng Wei2;  Tan Minjia1;  Bian Lishuang1
1 School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
2 School of Transportation, Southeast University, Nanjing 210096, China
Keywords:
intersection;  vehicle emission;  pollutants;  projection pursuit;  bat algorithm
PACS:
TP311
DOI:
10.3969/j.issn.1003-7985.2019.03.016
Abstract:
The projection pursuit model is used to study the assessment of air pollution caused by vehicle emissions at intersections. Based on the analysis of the characteristics and regularities of vehicle emissions at intersections, a vehicle emission model based on projection pursuit is established, and the bat algorithm is used to solve the optimization function. The research results show that the projection pursuit model can not only measure the air pollution of vehicle emissions at intersections, but also effectively evaluate the level of vehicle exhaust emissions at intersections. Taking the air pollution caused by vehicle emissions at intersections as the research object and considering the influence factors of vehicle emissions on air pollution comprehensively, the evaluation index system of vehicle emissions at intersections on air pollution is constructed. Based on large data analysis, a prediction model of air pollution caused by vehicle emissions at intersections is constructed, and an improved bat algorithm is used to realize the assessment process. The application results show that the prediction model of vehicle emissions at intersections can define the degree of air pollution caused by vehicle emissions, and it has good guiding significance and practical value for solving the problem of air pollution caused by vehicle emissions.

References:

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Memo

Memo:
Biography: Hu Qizhou(1975—), male, doctor, associate professor, qizhouhu@163.com.
Foundation items: The National Natural Science Foundation of China(No.51178157), High-Level Project of the Top Six Talents in Jiangsu Province(No.JXQC-021), Key Science and Technology Program in Henan Province(No.182102310004), the Humanities and Social Science Research Programs Foundation of the Ministry of Education of China(No.18YJAZH028).
Citation: Hu Qizhou, Deng Wei, Tan Minjia, et al. Projection pursuit model of vehicle emission on air pollution at intersections based on the improved bat algorithm.[J].Journal of Southeast University(English Edition), 2019, 35(3):389-392.DOI:10.3969/j.issn.1003-7985.2019.03.016.
Last Update: 2019-09-20