Abstract:
Abstract: - Abstract: - Highway traffic accidents are a main
community health problem unease ensuing millions fatalities
and million serious injuries in the world each year. In the
developing country like Ethiopia, is also the victim of road traffic
accident or crush causing deaths, property damage and serious
injuries. In order to analyses severity level of road traffic
accidents, data is important to find out factors that are related to
fatal, grievous, minor and non- injuries to gauge a fixed
variables that contributes towards forecast the severity level of
road traffic crashes. A lane traffic stream pound or impact
happens when a vehicle slams into another vehicle, passerby,
creature, or geological or building obstruction and result in
injury, property harm, and lethal/demise. Path traffic control
framework is, where basic information about the squash is
recorded and saved for looming use. Expending that information
the proposed examination have been extricated the contributing
elements of street auto collision and create prescient model to
foresee seriousness level for street car crash, wounds and
fatalities utilizing information mining methods.. The main task
of research is to make known the applicability of data mining
techniques in emerging a model to support road traffic accident
brutality analysis in preventing and extracting patterns that are
corresponding with road accident in different ways of
presentation methods. The road traffic accident historical data
,obtained from traffic Oromia police commission of East Shewa
Zone, Oromia and police commission of Federal government of
Ethiopia.
