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鸟击问题严重威胁航空器运行安全,给航空业造成了巨大的经济损失,为了有效预防民航鸟击事件的发生,根据数据挖掘理论,在分析民航鸟击事件关键诱发属性基础上,提出了一种基于FPGrowth算法的民航鸟击事件关联性分析方法。根据中国民航鸟击事件统计数据,挖掘出鸟击事件各属性间潜在的、有价值的关联,通过设置最小支持度和最小置信度,得出重要的关联性规则。结果表明,该方法根据历史数据可推测出导致鸟击事件发生的相关因素,改善了以往凭借专家经验的片面性、模糊性和不确定性。通过飞机发动机设计、颜色涂装等措施切断导致鸟击事件发生的相关因素,达到有效预防鸟击事件的效果,完善防治措施,最大限度地避免鸟类撞击航空器,保障民航运输安全。
The problem of bird strike seriously threatens the operation safety of aircraft and causes huge economic losses to the aviation industry. In order to effectively prevent the occurrence of bird strike in civil aviation, based on data mining theory, based on the analysis of the key inducing attributes of bird strike in civil aviation, Correlation Analysis of Civil Aviation Bird Combat Events Based on FPGrowth Algorithm. According to the statistical data of China Civil Aviation bird strike events, the potential and valuable correlations between the various attributes of the bird strike events are uncovered. By setting the minimum support degree and the minimum confidence level, important correlation rules are obtained. The results show that this method can deduce the relevant factors that lead to the bird strike incident according to the historical data and improve the one-sidedness, fuzziness and uncertainty of the past by virtue of expert experience. Through aircraft engine design, color coating and other measures to cut off the relevant factors that led to the bird strike incident, to effectively prevent the bird strike incident effect, improve prevention and control measures to maximize the avoidance of birds hit the aircraft to protect the safety of civil aviation transport.