Hybrid Machine Learning and Geographic Information Systems Approach — A Case for Grade Crossing Crash Data Analysis

DOI10.1142/S2424922X20500035zbMath1462.62750MaRDI QIDQ5858143

Ahmed Lasisi, Jian Chen, Pengyu Li

Publication date: 9 April 2021

Published in: Advances in Data Science and Adaptive Analysis (Search for Journal in Brave)

zbMATH Keywords

machine learninggeographic information systemsgrade crossing accidentsrailway/highway engineering

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Learning and adaptive systems in artificial intelligence (68T05) Statistical aspects of big data and data science (62R07)

Uses Software

• ArcMap
• ArcGIS
• Scikit
• ExSTraCS

Cites Work

• Risk assessment and risk management: review of recent advances on their foundation
• A flexible distribution class for count data
• An Introduction to Statistical Learning
• Unnamed Item
• Unnamed Item

This page was built for publication: Hybrid Machine Learning and Geographic Information Systems Approach — A Case for Grade Crossing Crash Data Analysis