Pan Liu – författare

Transportation Big Data: Theory and Methods is centered on the big data theory and methods. Big data is now a key topic in transportation, simply 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 the commonly used methods for handling transportation big data; it is supported by a wealth of transportation engineering examples, together with codes. It offers a concise, yet comprehensive, description of the 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