A Way to Assess Risk Factors in Residential Environment

Donghyok Suh, Jeonghwa Song
2014 unpublished
This paper recognizes life environment risks which variously exist to guarantee safety of users from all kinds of risk factors that do in resident environment and suggests a plan to infer degree of risk. The artificial neural network theory which makes a great contribution to the artificial intelligence and data-mining fields detects risk factors through mechanical learning even in the environment that cannot in advance recognize them and provides clues of good methods to be able to evaluate
more » ... degree of risk of real-life situations. The risk factors which exist in each residential environment are not uniform and there are many cases that don't have single factors. It's the plan which can suppose high level of each risk factor and risk environment by handling these various and multiple risk factors. This paper includes the pre-clustering to the risk calculation using the artificial neural network. It was confirmed that the risk calculation using the artificial neural network could be improved through a pre-clustering of the input data.
doi:10.14257/astl.2014.48.13 fatcat:7m5avoef65hvfg3kwsdfgxktwq