A State-Based Approach to Modeling Air Accidents Caused by Loss of Flight Control

In this research,the most important causes of helicopter accidents are discussed.For this aim,the data of aviation accidents that occurred in Iran and the data registered in ICAO are used.Several research efforts have been directed towards betters understanding the causes of accidents.Many of these efforts use ICAO accident reports and data.Unfortunately,while these studies easily identify the top types of accidents(e.g.,inflight loss of control (LOC)),they usually cannot identify why these accidents are happening.Most ICAOnarrative reports for accidents are very short(many are only one paragraph long),and do not contain much information on the causes(likely because the causes were not fully identified).Unfortunately,in our country, the efforts made in this field for various reasons have not been given much attention so far,which has led to the lack of clear and citationable results of the correct causes of aviation accidents.Aviation accidents in Iran,especially in the last two decades,do not show a significant reduction in the number of accidents or casualties.To better understand the causes of aviation accidents,this study offers a state-based approach to examining existing logical gaps or neglected cases and a computer program(in STATISTICA)that automatically builds states,signs,and information codes related to accidents These rules also help identify and count causes for accidents that were not discernable from previous analyses of historical accident data.State-based approach shows that distraction of pilots to objects in the environment often results in loss of flight control(16.7%),which is not directly distinguishable from conventional analysis.State-based modeling is a new method in this field.Also,machine learning tools are used to achieve more desirable results.