The Research Of Flight Normality Management Based On Operational Data Analysis

With the rapid development of China's civil aviation,the normalization of flight management which have plagued China's civil aviation for nearly a decade,and it become more and more concerned by consumers and medias;in particular,for the large-scale flight delays,if not deal properly it will become the focus of social concern.To this end,the country attaches great importance to require the normalization of flight management as a civil aviation industry's livelihood project.This paper is based on the normalization of flight management regulations,start from the four aspects of normal flight statistics,normal flight guarantee,delay handling and passenger management.It collects and analyzes the historical operating data of the AOC to find the main influencing factors.The actual operational data use to classify the main influencing factors and establish an early-warning mechanism for flight delays to ensure normal flight conditions.In response to delays in flights that have already occurred,relevant recovery strategies are found to improve passenger satisfaction and service quality.The main research work of this article is as follows:Base on the civil aviation regulations and airline survey data,and base on the normalization of flight management regulations,the relevant content of normal flight management is summarized.According to the regulations,the normal management of flights can be divided into three main areas: normal flight statistics,normal flight guarantees and delays.Flight statistics research.According to the actual flight daily operation data collect by visiting multiple airlines,base on actual operational data,the factors affecting the normality of flights is summarized according to the normal flight statistics method,and data are provided for the normal guarantees.Research on early warning mechanisms.Base on the influencing factors analyz in the previous chapter,an evaluation index is established,a fuzzy mathematics method is used to establish the model,an early warning mechanism for flight delays is constructed,and actual operational data is used for testing.Integration of aircraft and unit recovery studies.An integrate recovery model is established and the model solve using a strategy search method.Finally,the data is used to verify the model.Research on the restoration of passenger flow.The recovery model of passenger flow is constructed and solved by Danzig-Wolfe algorithm.Finally,it is verified by examples toprove the feasibility and effectiveness of the algorithm.