FLIGHT DEMAND FORECASTING MODEL BASED ON C-MEAN CLUSTERING ALGORITHM

Flight demand forecasting is the core technology for airline revenue management. This paper presents a new flight forecasting model that is based on C-mean clustering algorithm. The date and season attributes about the flight are discarded, and the complexity is reduced. Compared with the popularly used regression algorithm and pick-up algorithm, the new algorithm is faster, more robust and more accurate, and it has been applied to the real system of Xiamen Airlines.