Abstract
Bridges are important structures. Loading forces due to traffic volume and flow are important physical factors that affect the bridge's structural reliability. Thus, for safety assessments, it is important to monitor and study traffic volume. This chapter analyzes the traffic data on the 25 de Abril Bridge in Portugal. It aims to study the tail distribution. The chapter discusses: data under study, the extreme value methodology used in this work and extreme value models to infer the extremal behavior of the traffic volume. The objective of extreme value theory is to quantify the stochastic behaviour of extreme events, such as extreme climate events, a stock market crash or a new world record in athletics. Estimation of the model parameters is an important first step for further inference in the tail.
| Original language | English |
|---|---|
| Title of host publication | Data Analysis and Related Applications, Volume 1 |
| Subtitle of host publication | Computational, Algorithmic and Applied Economic Data Analysis |
| Editors | Konstantinos N. Zafeiris, Christos H. Skiadas, Yiannis Dimotikalis, Alex Karagrigoriou, Christiana Karagrigoriou-Vonta |
| Publisher | Wiley |
| Chapter | 5 |
| Pages | 57-66 |
| Number of pages | 10 |
| Volume | 9 |
| ISBN (Electronic) | 978-139416551-3 |
| ISBN (Print) | 978-139416550-6 |
| DOIs | |
| Publication status | Published - 26 Aug 2022 |
Keywords
- Abril bridge
- Extreme value methodology
- Extreme value theory
- Model parameters
- Tail distribution
- Traffic volume
