ROAD TRAFFIC ACCIDENT REDUCTION VIA GLM, CRT, LR REGRESSION MODELS

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PAKGOHAR ALIREZA; KHALILI MOHADESEH; SAFARZADEH MAHMOOD

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Journal Paper

Paper Information

Journal: DANESH-E-ENTEZAMI Year:2010 | Volume:12 | Issue:1 (46) Page(s): 77-106

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Information Journal Paper

Title

ROAD TRAFFIC ACCIDENT REDUCTION VIA GLM, CRT, LR REGRESSION MODELS

Author(s)

PAKGOHAR ALIREZA | KHALILI MOHADESEH | SAFARZADEH MAHMOOD | Issue Writer Certificate

Keywords

ROADS ACCIDENTSQ3

LOGISTIC REGRESSIONQ2

TREE REGRESSIONQ3

REGRESSIONQ2

AGREEMENT TABLESQ3

ACCIDENT INTENSITYQ3

Abstract

Traffic-related accident is one of the important issues which threaten public health. The problem is becoming more sophisticated in Iran and there are lots of young victims due to car accidents. In order to find out the effective factors in traffic accidents, REGRESSION models such as logistic models (LR), and CRT can be used.This article investigates the reasons of road traffic accident reduction when benefitting from GLM, CRT, LR REGRESSION models. The main three factors involved in accidents were known to be human, road, and car - related factors. Statistical samples were 343, 082 cases of Iran ROADS ACCIDENTS during the year of 2007.

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APA: Copy

PAKGOHAR, ALIREZA, KHALILI, MOHADESEH, & SAFARZADEH, MAHMOOD. (2010). ROAD TRAFFIC ACCIDENT REDUCTION VIA GLM, CRT, LR REGRESSION MODELS. DANESH-E-ENTEZAMI, 12(1 (46)), 77-106. SID. https://sid.ir/paper/100588/en

Vancouver: Copy

PAKGOHAR ALIREZA, KHALILI MOHADESEH, SAFARZADEH MAHMOOD. ROAD TRAFFIC ACCIDENT REDUCTION VIA GLM, CRT, LR REGRESSION MODELS. DANESH-E-ENTEZAMI[Internet]. 2010;12(1 (46)):77-106. Available from: https://sid.ir/paper/100588/en

IEEE: Copy

ALIREZA PAKGOHAR, MOHADESEH KHALILI, and MAHMOOD SAFARZADEH, “ROAD TRAFFIC ACCIDENT REDUCTION VIA GLM, CRT, LR REGRESSION MODELS,” DANESH-E-ENTEZAMI, vol. 12, no. 1 (46), pp. 77–106, 2010, [Online]. Available: https://sid.ir/paper/100588/en

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