Research On Data Distribution Fitting In Optimization Of Fuel Policy

With the development of science and technology,the reliability of aircraft is enhanced,airport infrastructure and ATC system is improved,operation control capability is continuo us ly enhanced,and the support capability of civil aviation safety operation continues to improve.Under the premise of ensuring safety,reducing the carrying capacity of fuel and reducing fuel consumption caused by excessive fuel can reduce the operation cost of airlines,reduce carbon dioxide emissions and promote the development of China's civil aviation.In recent years,civil aviation scholars in china and abroad have done a lot of research on the issue of fuel saving.The research direction is mainly focus on strengthening operational control,rationally choose the configuration of aircraft configuration,and rational al ocation of airspace resources,and put forward some opinions based on actual problems.With the demand for environme nt a l protection and improving the company's operating efficiency,active fuel policies are particularly important.Therefore,it is of practical significance and value to study the distribution of data in the optimiza tion of fuel policies.CCAR-121 has made changes to the fuel policy,put forward the same requirements for domestic and foreign fuels,confirmed the fuel composition and name,and proposed fuel for supplementary operations.Demand reductions,additions to the fuel requirements put forward under specific conditions,and improvements in the factors that should be taken into account in the calculation of the required amount of fuel,providing support to the regulations for the implementation of airline fuel po licy optimisation.Fuel policy optimization is based on statistical methods.When statistical analysis of fuel data can be more accurately describe the distribution of data,can choose a more scientific and unpredictable fuel policy for airlines,and better fit the actual operation of the company.Therefore,it is an indispensable and important step to study the distribution of fuel data.After collecting and analyzing a large number of QAR fuel data,it was found that fuel data has multiple peaks,thick tails,etc.,and the commonly used distribution model does not accurately fit the distribution of fuel data.This paper aims to study a model that can accurately describe the distribution of fuel data and provide a methodological reference for the data analysis part of fuel policy optimization.The Gauss mixture distribution model based on normal distribution is used in this paper.Normal distribution model is a commonly used model in statistical analysis.Although the model can not directly and accurately fit the distribution of fuel data,many of the data in life are in normal distribution.It is a common distribution model.Therefore,we can simplify the difficult problem,so we can use multiple normal distribution to superimpose the fuel data.The particle swarm optimization(PSO)is used to estimate the parameters.The method is used to find the optimal solution by multiple iterations.It has the characteristics of simpler rules,easier implementation,higher accuracy and faster optimization than other algorithms.In addition,the fuel consumption data is relatively large,so we will code the algorithm based on Matlab platform to better improve the fitting efficiency.After the analysis of the examples,it is found that the proposed model can accurately fit the fuel data,and more accurately describe the distribution of fuel data,and verify the availability of the proposed model.