Aircraft Crash Analysis Using Data Mining Techniques

An aviation accident is an event in which an aircraft is severely damaged/lost/inaccessible or resulting in a serious/fatal injury during flight operations. It is very important in aviation to learn lessons from past aircraft crashes for continuous improvement and accident prevention. This paper discusses the aircraft crashes in the world that occurred in the last century and analyzed them in depth to reveal the possible causes based on the facts. The historical data set used for analysis includes categorical/verbal data such as aircraft types, flight routes, and cockpit voice recordings (VCR), as well as numerical data such as year, number of passengers, number of deceased passengers, and flight parameters records (FDR). Various machine learning algorithms and data science techniques were applied for the analysis of aircraft accident data, and comprehensive analysis and comparison were made. Our multi-year analysis will also help discern changes in causal trends over the past two decades. Our analysis also highlights the most likely causes such as cockpit management and mechanical issues.