%0 Journal Article %A CAO Weidong1 %A 2 %A XU Daidai2 %A WANG Jing2 %A WANG Jialiang2 %T NOSHOW Prediction and Strong Factor Association Analysis in Civil Aviation %D 2019 %R 10.3778/j.issn.1002-8331.1709-0387 %J Computer Engineering and Applications %P 221-227 %V 55 %N 2 %X In business of civil aviation, the phenomenon that passengers cannot be scheduled after reservations(NOSHOW) has been the unsolved problem in terms of airline revenue loss. In order to solve the problem, a method of NOSHOW prediction and strong factor association analysis in civil aviation is proposed. Firstly, the NOSHOW decision tree is modeled by improved C5.0 algorithm, and the quantified results of NOSHOW correlation factor are obtained. Then, the association rule mining of NOSHOW strong factor is carried out by Apriori algorithm. The NOSHOW decision tree model with accuracy of 99.75% is constructed, and 139 factor association rules with confidence above 80.054% and support over 10.021% are obtained, which further reveals the implicit correlation relationship between NOSHOW strong factors, besides it also provides an effective decision-making basis for major airlines to implement accurate NOSHOW prediction and revenue enhancement management. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1709-0387