Work

Predicting Operating Train Delays into New York City using Random Forest Regression and XGBoost Regres-sion Models

Year: 2023

Type: article

Abstract: The Long Island Railroad operates one of the largest commuter rail networks in the U.S.[1]. This study uses data which includes the location and arrival time of trains based on onboard GPS position and other internal sources. This paper analyzes the GPS position of the train to gain insight into potential gaps in on time performance and train operations. This was done by developing a Random Forest Re-gression model [2] and an XGBoost regression model [3[. Both models prove to be useful to make such predictions and should be used to help railroads to prepare and adjust their operations.

Source: International Journal of Engineering Business and Management

DOI: 10.22161/ijebm.7.1.5

Author: Thomas Wiese

Institution: Empire State University

Language: English

Topic: Railway Systems and Energy Efficiency

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4323341447