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机构地区:[1]中国民航大学计算机科学与技术学院,天津300300 [2]中国民航信息科研基地,天津300300
出 处:《计算机应用与软件》2016年第11期21-23,61,共4页Computer Applications and Software
基 金:国家自然科学基金项目(60879015);中国民航科技重大专项(MHRD201241)
摘 要: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 civil aviation in our country,the major hub airports have accumulated massive flight cooperative security data,and it is of significant meaning to mine the potential hidden knowledge in them. Aiming at this issue,we combine the airport flight cooperative security business regulations with the features of flight cooperative security data,mined the knowledge hidden in flight cooperative security data by using association rule mining technology,and further got the help from the mined knowledge to optimise flight security process and to improve the quality of airport service support. It is verified trough example that the association rule algorithm can well mine the potential knowledge hidden in flight cooperative security data,and the application of it in practices can provide effective support and decision-making basis for optimising the flight security process,increasing the flight punctuality,and enhancing the capability of airport service support.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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