Applying data mining to extract damage level of bird strike on helicopters

Underestanding the risk factors of damage will be helpful to mitigate damage of bird strike. Planning for preventing bird strike evidence need to risk factors and relation of these factors to level of damage. Hence, the goal of this paper is extracting the risk factors by consideration of damage level imposed on helicopters. The data source of the current research is the Federal Aviation Administration Wildlife Strike Database which was gathered for about twenty years. In this paper, we used four kind of decision tree algorithms included C5.0, CART, C&R TREE, and QUEST to extract damage level of bird strike (D, S, M, and N that demonstrate of destroyed, substantial, minor, and not defined) on helicopters. The results demonstrated that bird size, helicopters type, phase of flight, speed, and type of engine are the most important risk factors causing damage to helicopters, respectively. Finally the research concludes with some suggestions to reduce damage of bird strike on helicopters.