| Garbage classification is a breakthrough to solve the worsening situation of the increasingly serious domestic garbage situation.How to encourage the residents to participate in garbage classification and improve the quality of garbage classification is an urgent concern for the government in our country.In recent years,with the continuous penetration of information technology,intelligent identification and data analysis technology has been applied to garbage classification.Based on this,this paper aims to empirical analysis of the living garbage classification data,data analysis and the combination of social governance,based on real data driven,using Rank Net and RFM model prediction method,based on integral incentive system of garbage classification effect is analyzed,and the factors affecting the garbage classification based on the behavior of the simulation,To explore the influence of users’ enthusiasm for household garbage classification,in order to provide a reference for improving the quality of household garbage classification in communities.The specific work of this paper is as follows:(1)Analysis of the influencing factors of garbage classification based on the incentive system of points.Through correlation analysis,this chapter discusses the situation of public supervision,organizational implementation and publicity work and puts forward corresponding reasonable suggestions.Among them,public supervision refers to whether residents deliver garbage is closely watched or not,that is,face,which indicates that the concept of face has a significant promoting effect on domestic garbage disposal behavior.The implementation of the organization is represented by four key indicators(registration rate,participation rate,accuracy rate and separation rate),which are discussed through the time change trend and correlation analysis of key indicators.Through the correlation analysis of the total number of door-to-door publicity and four key indicators,the specific effects of publicity work are discussed.The results show that door-to-door publicity contributes to the increase of registration rate,but the effect on participation rate and accuracy rate remains to be improved.(2)Waste classification effect analysis based on the incentive system of points.Starting from garbage delivery data,users are classified according to RFM model,Rank Net prediction is introduced,and the order of garbage delivery and The Times of goods exchange are taken as the characteristic values of prediction to predict the user category of the residents in the next month.According to Rank Net prediction results,introducing The Times of goods exchange on the basis of orderliness can significantly improve the accuracy of prediction,which verifies the effectiveness of the incentive system of garbage classification points,and provides support for the continuous promotion of the incentive system of garbage classification points in terms of data.(3)Incentive behavior analysis of garbage classification based on multi-agent simulation.Based on Schelling model and game of life model,a multi-agent simulation model of user value transformation is established,which is mainly built around subjective norms,classification knowledge and classification attitude,in order to explore the influence of individual intrinsic factors on residents’ enthusiasm in participating in garbage classification.The simulation results show that residents’ enthusiasm for garbage delivery is affected by subjective norms,that is,there is an interactive relationship between "You become who you spend your time with".Both classification knowledge and classification attitude are positively correlated with residents’ enthusiasm for garbage delivery.In view of this,this paper puts forward policy suggestions to do a good job in publicity work,improve residents’ classification knowledge level,make proper use of subjective norms,carry out differentiated incentive measures,strengthen classification attitude with fairness,and improve the incentive effect. |
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