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

BAYATA H. F., Bayrak O. Ü., Pehlivan H.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.27, sa.4, ss.2290-2298, 2018 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 27 Sayı: 4
  • Basım Tarihi: 2018
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.2290-2298
  • Anahtar Kelimeler: Number of Traffic Accident, Statistical Modeling, Artificial Neural Network, Multivariate Regression Analysis, Turkey North Transit Interurban, PREDICTION MODELS, REGRESSION, SAFETY, SERIES, ROADS
  • Erzincan Binali Yıldırım Üniversitesi Adresli: Evet

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.