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Prediction And Research Of Short-time Passenger Flow In China Mobile's Business Halls In Jinan

Posted on:2020-06-13Degree:MasterType:Thesis
Country:ChinaCandidate:D DongFull Text:PDF
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China Mobile's business hall is one of the three windows of China Mobile.As China Mobile's direct service to customers,it plays an important role in promoting corporate image,marketing mobile business and consolidating the market.In the future,with the advancement of society,the upgrading of consumption and the development of the Internet of Things,the mobile business hall needs to be transformed.It is necessary to weaken its sales function and strengthen its service and display functions.This is the choice of the times and history.In the business hall satisfaction survey,;"customer waiting time is too long" is a difficult problem to solve,because the amount of customers who go to the mobile business hall to conduct business every day is different,resulting in different opening windows of the business hall,and the number of assigned staff is different.More accurate prediction of the number of short-term arrivals is the key to the study.The business hall can reasonably allocate the service personnel in the hall according to the predicted passenger flow,do a good job of diversion marking,and improve work efficiency and service satisfaction.It can be seen that it is of great market significance to establish a statistical model for customer tra:ffic statistics through business data analysis.Based on abundant domestic and external related documents,this article takes the daily traffic to the hall in the mobile business hall of Tianqiao District,Jinan City from March 1st to August 10th,2018 as a training set.The time series model and the parameters of the model are determined according to the characteristics of the ornginal data.At the same time,the sequence is predicted by the gray Markov model,Furthermore,the prediction results are compared with the Grey Markov prediction results.Finally,the two models are combined by the residual accumulation method,and the weight coefficients are changed so that the selected model can Better describe the trend of the original data,and have a better prediction effect.This paper uses the selected model to analyze and study the future passenger flow of the business hall.The combination of theory and practice verifies the feasibility of the method selected in this paper,and has certain guiding significance for the research on the future changes of the business department's passenger flow sequence.
Keywords/Search Tags:ARIMA(p,d,q), Grey Theory, Markov, Combined Model, Relative Error
PDF Full Text Request
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