Quantitative Analysis Of The Influence Of Social Economy On Public Transportation Based On Parallelized Bagging Bayes

With the development of social economy,many urban public transportation facilities can not meet people's growing travel needs,and reasonable improvement of public transportation has become a hot topic.The main factor affecting public transportation is the state of social and economic development.The main goal of developing public transportation is to meet the needs of social and economic development.Therefore,it is necessary to study whether the public transportation situation meets the needs through the status quo of social economic development,and with the development of social economy,public transportation.It should also be adjusted accordingly.Due to the complex relationship between social economy and public transportation,it is impossible to directly use the socio-economic evaluation of the development of public transportation.Therefore,this paper proposes the Bagging Bayesian model to quantitatively study the impact of social economy on public transportation.Public transportation and socio-economic data are vector data distributed in geospatial space.Since vector data cannot meet the needs of quantitative analysis in this paper,it is necessary to convert these vector data into raster data.However,after the vector data is expressed by the raster data,the amount of data will become very large.In order to improve the computing performance,MapReduce parallel computing is used for processing.The main work and research contents of this paper are as follows:(1)The MapReduce parallel computing is proposed to improve the computational performance of raster data in public transportation and social economy.The MapReduce raster image calculation is divided into three steps.The structure is first reorganized using a structure for data integration.The second is to parallelize the quantitative analysis of the integrated data.Finally,the calculation results are recomposed into a graph to visualize the research on the impact of social economy on public transportation.Through experiments,it is found that the parallelized quantitative analysis calculation speed is significantly better than the stand-alone calculation speed.(2)The public transport convenience indicator is used to measure the development of public transportation.This paper uses the clustering method to divide the bus convenience.Firstly,this paper uses principal component analysis to remove the data overlap between the data factors of public transportation data.The results show that the clustering quality after the data of each factor is removed is better than the data overlapping cluster without the removal factor.Secondly,use Calinski-Harabasz to find the optimal number of clustering clusters and verify the quality of principal component analysis.Finally,use Kmeans to divide bus convenience.(3)Bagging is used to integrate several Bayesian(MNB)classifiers to improve the MNB classifier,thereby improving the quantitative analysis of the impact of social economy on public transportation.After analysis,it is found that there are some factors in the socio-economic relationship,which have an impact on the classification of MNB.Using Bagging to integrate MNB and randomly selecting socioeconomic factors can eliminate the relationship between factors.Through the quantitative analysis of social and economic impacts on public transportation,it is found that the parallelized Baging Bayesian classification effect is significantly better than the parallelized MNB,which is not worse than the BP neural network classification effect.In this paper,the development of public transportation is measured by the convenience of public transportation.From the influencing factors of public transportation(social economy),the parallel Bagging Bayesian(MNB)model is used to train and express the complex relationship between public transportation and social economy.On the grid map,the public transportation and socio-economic relations are accurately expressed,so that the influence of social economy on the development of public transportation is studied in detail in geospatial space.Through quantitative analysis experiments on the impact of social economy on public transportation in the high-tech zone,it is found that public transportation along the subway in the high-tech zone does not meet the needs of social and economic development,and it is necessary to vigorously develop public transportation.