Binding: Paperback
Description: Transportation is a combination of systems that presents a variety of challenges often too intricate to be addressed by conventional parametric methods. Increasing data availability and recent advancements in machine learning provide new methods to tackle challenging transportation problems. This textbookis designed for college or graduate - level students in transportation or closely related fields to study and understand fundamentals in machine learning. Readers will learn how to develop and apply various types of machine learning models to transportation - related problems. Example applications include traffic sensing data - quality control traffic prediction transportation asset management traffic - system control and operations and traffic - safety analysis.
Title: Machine Learning For Transportation Research And Applications
Author(s): Ke Ruimin (Assistant Professor Department Of Civil Engineering University Of Texas At El Paso Usa.)
Publisher: Elsevier - Health Sciences Division
Barcode: 9780323961264
Pages: 252 Pages
Publication Date: 4/25/2023
Category: Machine Learning