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随着我国民航业的迅猛发展,各大枢纽机场累积了海量的航班协同保障数据,挖掘其中潜在隐藏的知识具有重要意义。结合机场航班协同保障业务规则及航班协同保障数据的特征,利用关联规则挖掘技术,挖掘隐藏在航班协同保障数据中的知识,进而借助其优化航班保障流程,提升机场服务保障质量。通过实例验证,关联规则算法能够较好地发掘隐藏在航班协同保障数据中的潜在知识,将其应用于实际中能够为优化航班保障流程、提高航班准点率、提升机场服务保障能力提供有效的支撑和决策依据。
With the rapid development of China’s civil aviation industry, the major hub airports have accumulated a large amount of flight coordination and security data, mining the potential hidden knowledge of great significance. Combining with the business rules of airport flight coordination security and the characteristics of the flight coordination guarantee data, the association rule mining technology is used to mine the knowledge hidden in the flight coordination guarantee data and then optimize the flight support process to improve the quality of airport service support. Through the example verification, the association rule algorithm can better discover the latent knowledge hidden in the flight coordination guarantee data, which can effectively support the optimization of the flight guarantee process, improve the on-time flight rate and enhance the service support ability of the airport. And decision-making basis.