Research On Flight Bank Based On Gene Expression Programming For Hub Airports

With the increasing growth in air traffic, the impact of the air transport industry in the international exchange and national life becomes increasingly important. It’s a wide problem to measure the efficiency of the transit hub effectiveness in the airports of our country. The wave design of fights is an important way to solve the key scientific problems of measuring the efficiency of the transit hub benefits. With the natural biological evolution law as the core, GEP is a new generation of adaptive evolutionary algorithm depending on computer programming technology. GEP is analyzed and designed to find the functions of flights wave model.Firstly, according to flight departure wave into separate concept, the ideal flight wave model has been proposed to analyze and calculate the biggest flight wave ideal model based on transit opportunity, to optimize the theory of flights wave model according to the airport operation efficiency and capacity of space, to analyze the features of calculation model and to conclude the monotonically decreasing wave theory of flight arrivals and departures optimized waveform wave form optimization.Secondly, basic background, algorithm design process and key factors of gene expression programming algorithm was introduced to implement the improvement of traditional GEP algorithm with a variety of evolutionary convergence strategy.Finally, according to the monotonically decreasing characteristics of theory optimization waveform, the flight time were simple sorting to calculate transit opportunities and verify its superiority in improving transit opportunities. Meanwhile, depending on the simple flights date of Beijing airport and object function of transit opportunities, gene expression programming algorithm was designed to find the flights wave function. The corresponding time function value of airport flight data was taken into consideration to operate the monotonic analysis of function and to verify apophatically the applicability and feasibility of the theoretical optimized waveform.