Comparison of weighted and simple linear regression and artificial neural network models in freeway accidents prediction (Case study: Qom & Qazvin Freeways in Iran)

2nd International Conference on Computer and Network Technology, ICCNT 2010

Volumn , Issue , 2010, Pages 392-396

  Mahmoudabadi, Abbas ^a  

^a PAYAME NOOR UNIVERSITY   (Iran)

Author keywords

Artificial neural network; Freeway; Linear regression; Rural accidents; Surface condition; Traffic volume

Indexed keywords

ACCIDENT DATA; ANALYTICAL PROCESS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; FREEWAY; HEAVY TRAFFICS; INPUT VARIABLES; MINIMUM MEAN SQUARE ERRORS; PERFORMANCE COMPARISON; PREDICTION MODEL; PRINCIPLE COMPONENT; PRINCIPLE COMPONENT ANALYSIS; SIMPLE LINEAR REGRESSION; SURFACE CONDITIONS; TRAFFIC VOLUMES;

ACCIDENTS; BLOCK CODES; COMPUTER NETWORKS; ELECTRONIC DOCUMENT IDENTIFICATION SYSTEMS; ERRORS; LINEAR REGRESSION; MATHEMATICAL MODELS; MEAN SQUARE ERROR;

NEURAL NETWORKS;

EID: 77954318219     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCNT.2010.73     Document Type: Conference Paper

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