CHARACTERISTICS AND ESTIMATION OF TRAFFIC ACCIDENT COUNTS USING ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE ANALYSIS: A CASE STUDY IN TURKEY NORTH TRANSIT INTERURBAN

Bayata, Halim Ferit; Bayrak, Osman Ünsal; Pehlivan, Hüseyin

Makale Tam Makale Uluslararası 2018

CHARACTERISTICS AND ESTIMATION OF TRAFFIC ACCIDENT COUNTS USING ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE ANALYSIS: A CASE STUDY IN TURKEY NORTH TRANSIT INTERURBAN

Halim Ferit Bayata, Osman Ünsal Bayrak, Hüseyin Pehlivan

FRESENIUS ENVIRONMENTAL BULLETIN Cilt 27 · Sayı 4 · ss. 2290–2298 · 01.01.2018

Özet

By the World Health Organization, traffic accidents in 2013 have been identified as "human-caused natural disaster". Since the parameters which cause traffic accidents are numerous, they have a complex structure and they have continuously been a source of interest for analysis by researchers.

Anahtar kelimeler

SERIES SAFETY REGRESSION Artificial neural network Number of Traffic Accident Statistical Modeling Multivariate Regression Analysis Turkey North Transit Interurban PREDICTION MODELS ROADS

Sürdürülebilir Kalkınma Amaçları

SKA 3: Sağlıklı Bireyler

Atıf için künye

Bayata, H. F., Bayrak, O. Ü., & Pehlivan, H. (2018). CHARACTERISTICS AND ESTIMATION OF TRAFFIC ACCIDENT COUNTS USING ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE ANALYSIS: A CASE STUDY IN TURKEY NORTH TRANSIT INTERURBAN. FRESENIUS ENVIRONMENTAL BULLETIN, 27(4), 2290–2298.

BibTeX

@article{bayata2018-185016,
  author = {Bayata, Halim Ferit and Bayrak, Osman Ünsal and Pehlivan, Hüseyin},
  title = {CHARACTERISTICS AND ESTIMATION OF TRAFFIC ACCIDENT COUNTS USING ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE ANALYSIS: A CASE STUDY IN TURKEY NORTH TRANSIT INTERURBAN},
  journal = {FRESENIUS ENVIRONMENTAL BULLETIN},
  year = {2018},
  volume = {27},
  number = {4},
  pages = {2290--2298},
  issn = {1018-4619},
  url = {https://akademik.atauni.edu.tr/yayinlar/185016-characteristics-and-estimation-of-traffic-accident-counts-using-artificial}
}