Mathematical Modeling Methods and Their Application in the Analysis of Complex Signal Systems

Li, Yanjun and Chen, Miaochao (2022) Mathematical Modeling Methods and Their Application in the Analysis of Complex Signal Systems. Advances in Mathematical Physics, 2022. pp. 1-10. ISSN 1687-9120

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Abstract

Mathematical models are effective means of answers established by humans to solve real-world problems. Complex wireless communication can establish information interaction between vehicles, in order to reduce the delay time of the coordination control optimization timing scheme in coordination delay time. For smart car driving, a complex signal system, this study first establishes a relevant mathematical model. It is used to compare three mathematical models commonly used today. The results obtained under the same conditions show that the mathematical model is better in dealing with the complex signal system in terms of transmission accuracy in all segments. A number of vehicles in different states of the traffic system are selected, and the relevant data are collected to plot ROC curves using the mathematical model. It can be concluded that the freer and more complex the movement behavior of the vehicle, the greater the load it imposes on the road and the system. The results of the confusion matrix show that the model can effectively reduce the pressure on the road and the signal system. With the starting objective of smooth operation of public transportation, the target values are optimized by layering, and finally, the regional roadway capacity is effectively converged. Then, the mathematical model optimization of complex wireless systems and intelligent transportation networks is quantitatively evaluated. The optimized timing scheme through coordinated control achieves the expected effect in coordinated control of delay time and also reduces the average delay time of all intersections of the road network.

Item Type: Article
Subjects: Apsci Archives > Mathematical Science
Depositing User: Unnamed user with email support@apsciarchives.com
Date Deposited: 23 Jan 2023 07:11
Last Modified: 16 Nov 2023 05:53
URI: http://eprints.go2submission.com/id/eprint/93

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