Transportation Big Data: Theory and Methods is centered around big data theory and methods. As big data is now a key topic in transport because the volume of data has increased exponentially due to the growth in the amount of traffic (all modes) and detectors, this book provides a structured analysis of commonly used methods for handling transportation big data. It is supported by a wealth of transportation engineering examples with codes. The book offers a concise, yet comprehensive description key techniques and important tools in transportation big data analysis.
- Covers big data applications in transportation engineering in real-world scenarios
- Shows how to select different machine learning algorithms for processing, analyzing, and modeling transportation data
- Provides an overview of the fundamental concepts of machine learning and how classical algorithms can be applied to transportation-related problems
- Provides an overview of Python's basic syntax and commonly used modules, enabling practical data analysis and modeling tasks using Python
