Paper Titles

Numerical Simulation Analysis of Beam-Reduction and Rib-Addition Strengthening Method of Hollow Slab Bridges
p.57

Study on Topology Optimization for High Dynamic Flight Simulator Based on Hyperworks
p.66

Theory and Modeling Study on Deep Water Heave Compensation System
p.72

Response Analysis of Heaving Motions of Deep-Sea Installation Workboat
p.78

Intelligent Vehicle Coordination Model Based on Back-Propagation Network
p.84

Study of Safety Influence Factor of Bridge Substructure in Loess Gulch
p.89

Engine Fault Diagnosis Based on Support Vector Machine and Noise Analysis
p.97

Alternating Stress Dynamics Analysis of Harmonic Gear Flexible Wheel
p.102

Numerical Simulation and Test Study on Non-Preheating Welding Technology of HSLA Q550 Applied to Hydraulic Structures
p.110

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 546-547Intelligent Vehicle Coordination Model Based on...

Intelligent Vehicle Coordination Model Based on Back-Propagation Network

Article Preview

Abstract:

This thesis firstly introduces Back-Propagation Network, the model for the theory and the common process. And we view from two perspectives: the running hour of vehicles and passenger distributed capacity, and adopt Back-Propagation Network into vehicle coordination. We prove that coordination based on Back-Propagation Network is correct through examples.

You might also be interested in these eBooks

Electrical Insulating Materials and Electrical Engineering

Info:

Periodical:

Advanced Materials Research (Volumes 546-547)

Pages:

84-88

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.546-547.84

Citation:

Cite this paper

Online since:

July 2012

Authors:

Hai Ying Liu, Ya Qin An, Xia Yang, Kai Yin

Keywords:

Back-Propagation Network, Vehicle Coordination

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Zhu shun-ying, Wang hong, Xiang hong-yan. Traffic Flow Parameter and Traffic Incident Dynamic Forecast Method[M]. SEU Press, (2008).

[2] Jiang gui-yan. Technologies and Applications of Identification of Road Traffic conditions. [M]. China Communications Press, (2004).

[3] Jiao su-cheng. System Theory of neural network[M]. Xi'an UESTC Press, 1996: 1-36.

[4] Xu dong, Wu zheng. System Analysis and Design Based on MATLAB6. X –Neutral Network. Xi'an UESTC Press, 2002: 130.

[5] MANOEL C N. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions[J]. Expert System Applications'2009(36): 6164-6173 Expected approaches to coordinate 10000 01000 10000 00100 10000 01000 10000 00100 10000 01000 10000 00010 00010 10000 1 Formal Buses.

DOI: 10.1039/c8cc90392a

637 -0. 331.

[1] 073 -0. 015.

981 -0. 135.

[1] 093.

315.

681 -0. 143.

877.

077.

050.

[1] 210 2 Buss covering part of the routine.

383.

[1] 364 -0. 063 -0. 028 -0. 452.

[1] 105.

015.

011.

262.

[1] 152.

060.

076.

050 -0. 129 3 expresss -0. 117 -0. 016 -0. 021.

984.

044.

069.

211.

987 -0. 089.

140.

068 -0. 182.

128 -0. 278 4 On-time control -0. 051.

127 -0. 105 -0. 027 -0. 312 -0. 109.

010.

113.

233 -0. 146.

140.

[1] 083.

886 -0. 129 5 Busrelease.

271.

021.

022.

111.

073 -0. 056.

176 -0. 053 -0. 178 -0. 217.

245 -0. 189.

128 -0. 189 The actual coordination 10000 01000 10000 00100 10000 01000 10000 00100 10000 01000 10000 00010 00010 10000 Note: In coordination approaches, 10000" means formal buses, "01000" means "Buses covering part of the routine, "00100" means "expresses", "00010" means "on-time control" and "00001" means "bus release.

DOI: 10.1039/c8cc90392a