Gaining Insights into Traffic Data through Genetic Improvement

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Ekart:2017:GI,

• author = "Aniko Ekart and Alina Patelli and Victoria Lush and Elisabeth Ilie-Zudor",
• title = "Gaining Insights into Traffic Data through Genetic Improvement",
• booktitle = "GI-2017",
• year = "2017",
• editor = "Justyna Petke and David R. White and W. B. Langdon and Westley Weimer",
• pages = "1511--1512",
• address = "Berlin",
• month = "15-19 " # jul,
• publisher = "ACM",
• keywords = "genetic algorithms, genetic programming, genetic improvement, symbolic regression, data mining",
• isbn13 = "978-1-4503-4939-0",
• URL = "http://geneticimprovementofsoftware.com/wp-content/uploads/2017/05/ekart2017_road_data.pdf",
• URL = "https://publications.aston.ac.uk/id/eprint/31438/1/Road_traffic_data_through_genetic_improvement.pdf",
• URL = "http://eprints.sztaki.hu/9290/",
• DOI = "doi:10.1145/3067695.3082523",
• size = "2 pages",
• abstract = "We argue that Genetic Improvement can be successfully used for enhancing road traffic data mining. This would support the relevant decision makers with extending the existing network of devices that sense and control city traffic, with the end goal of improving vehicle flow and reducing the frequency of road accidents. Our position results from a set of preliminary observations emerging from the analysis of open access road traffic data collected in real time by the Birmingham City Council.",
• notes = "Last author also know as Angyalka Ilie Zudor Also known as \cite{sztaki9290}",

}

Genetic Programming entries for Aniko Ekart Alina Patelli Victoria Lush Elisabeth Ilie-Zudor

Citations