Single airline passenger arrival model in security area based on GMM

Abstract

Abstract:

GMM（Gaussian mixture distribution model）is used for a certain airline passenger arrival distribution fitting analysis. The extremum clustering method is adopted for the premiere distribution inspection of EM algorithm,parameter solution can be got after several iterations. In experimental part, a real airline check-in output data is adopted for experimental verification. Results show that the fitting precision of Gaussian mixture distribution is 90% or more. Compared with common fitting methods, the fitting precision is improved by more than 15%.Compared with extremum clustering and commonly used K means clustering of chi-square Gaussian mixture distribution model, the extremum clustering model has higher accuracy by about 5%.

Key words: single airline, Gaussian mixture distribution, EMalgorithm, extremum clustering

CLC Number:

V351.17

YU Zhijing, BAO Linlin, LUO Qian. Single airline passenger arrival model in security area based on GMM[J]. .

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