한국지구물리탐사학회:학술대회논문집
- 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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- Pages.252-254
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- 2003
The application of neural network system to the prediction of pollutant concentration in the road tunnel
- Lee, Duck-June (Inha University) ;
- Yoo, Yong-Ho (Inha University) ;
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Kim, Jin
(Inha University)
- 발행 : 2003.11.01
초록
In this study, it was purposed to develop the new method for the prediction of pollutant concentration in road tunnels. The new method was the use of artificial neural network with the back-propagation algorithm which can model the non-linear system of tunnel environment. This network system was separated into two parts as the visibility and the CO concentration. For this study, data was collected from two highway road tunnels on Yeongdong Expressway. The tunnels have two lanes with one-way direction and adopt the longitudinal ventilation system. The actually measured data from the tunnels was used to develop the neural network system for the prediction of pollutant concentration. The output results from the newly developed neural network system were analysed and compared with the calculated values by PIARC method. Results showed that the prediction accuracy by the neural network system was approximately five times better than the one by PIARC method. ill addition, the system predicted much more accurately at the situation where the drivers have to be stayed for a while in tunnels caused by the low velocity of vehicles.
키워드