Research On The Master Budgeting Management Of Chinese Airlines Based On The Data Mining

Due to the increasingly fierce competition in the civil aviation industry, airlines in our country must improve their management comprehensively by use of advanced management methods. Master Budgeting Management, which is one of the few management instruments that can combine all the key matters into a system, is attracting airlines attentions. Many domestic airlines have recognized the necessity to implement master budgeting management and also actively put it into effect. However, there is a great deal of practical problems confining its avail.Analysis regarding airlines'master budgeting management characters and nature of data mining provides the theory basis. By combining theory with practice, it discusses the major problems incurred in the operation of master budgeting management in accordance with its status quo, then puts forward new methods for preparing budgets based on the theory of data mining, and exemplifies the feasibility of these methods as well.Passenger-kilometres, aviation fuel prices, exchange rates are taken as three representative forecasting indicators which are fixed through the income statement. According to these indicators'specific characteristics,three different mathematical models (Artificial Neutral Networks Model, Auto Regressive Integrated Moving Average Modle and Auto-Regressive Modle) are established respectively based on the theory of data mining. The processes of forecasting are operated by software tools of Matlab and SAS. The new methods based on the data mining can make forecasting more scientific, accurate and convenient. It can improve airlines performance on master budgeting management, and facilitate airlines to make effective decisions and counteract market risk.