
Data Analysis in Pavement Engineering
Methodologies and Applications
- 1st Edition - November 6, 2023
- Imprint: Elsevier
- Authors: Qiao Dong, Xueqin Chen, Baoshan Huang
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 5 9 2 8 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 9 2 9 - 9
Data Analysis in Pavement Engineering: Methodologies and Applications introduces thetheories and methods as well as definitions, principles, and algorithms of data analysis… Read more

Purchase options

Institutional subscription on ScienceDirect
Request a sales quoteData Analysis in Pavement Engineering: Methodologies and Applications introduces the
theories and methods as well as definitions, principles, and algorithms of data analysis applied
in pavement and transportation infrastructure analysis, tests, maintenance, and operation.
This book provides case studies that demonstrate how these methods can be applied to
solve problems in pavement engineering. Through these real-life examples, readers can gain
a better understanding of how to utilize these data analysis techniques effectively.
Data Analysis in Pavement Engineering: Methodologies and Applications serves as a
reference for engineers or a textbook for graduate and senior undergraduate students in
disciplines related to transportation infrastructure.
- This book is the first comprehensive resource to cover all potential scenarios of data analysis in pavement and transportation infrastructure research, including areas such as materials testing, performance modeling, distress detection, and pavement evaluation.
- It provides coverage of significance tests, design of experiments, data mining, data modeling, and supervised and unsupervised machine learning techniques.
- It summarizes the latest research in data analysis within pavement engineering, encompassing over 300 research papers.
- It delves into the fundamental concepts, elements, and parameters of data analysis, empowering pavement engineers to undertake tasks typically reserved for statisticians and data scientists.
- The book presents 21 step-by-step case studies, showcasing the application of the data analysis method to address various problems in pavement engineering and draw meaningful conclusions.
Chapter 1 Pavement Performance Data
Chapter 2 Fundamentals of statistics
Chapter 3 Design of experiments
Chapter 4 Regression
Chapter 5 Logistic regression
Chapter 6 Count data models
Chapter 7 Survival analysis
Chapter 8 Time series
Chapter 9 Stochastic process
Chapter 10 Decision trees and ensemble learning
Chapter 11 Neural networks
Chapter 12 Support vector machine and k-nearest neighbors
Chapter 13 Principal component analysis
Chapter 14 Factor analysis
Chapter 15 Cluster analysis
Chapter 16 Discriminant analysis
Chapter 17 Structural equation model
Chapter 18 Markov chain Monte Carlo
- Edition: 1
- Published: November 6, 2023
- No. of pages (Paperback): 376
- Imprint: Elsevier
- Language: English
- Paperback ISBN: 9780443159282
- eBook ISBN: 9780443159299
QD
Qiao Dong
XC
Xueqin Chen
BH