Energy Consumption Prediction of Trams Based on Grey Relational Analysis and Regression Model
Zhipeng Yan, Yongzhi Min
Abstract
Zhipeng Yan, Yongzhi Min
Abstract
Aiming at the lack of quantitative analysis of the significant factors affecting the energy consumption of traditional tramway system energy consumption prediction methods, this paper proposes a method for predicting the energy consumption of trams based on the grey correlation analysis method and multiple linear regression model. The grey relational analysis method is used to calculate the correlation degree of energy influencing factors, and then the factors that have more significant impact on energy consumption are selected as the model input variables to establish the tram energy model. The experimental verification shows that the prediction method proposed in this paper can more accurately predict the energy consumption of trams and provide some references for the energy conservation management of trams.
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Aiming at the lack of quantitative analysis of the significant factors affecting the energy consumption of traditional tramway system energy consumption prediction methods, this paper proposes a method for predicting the energy consumption of trams based on the grey correlation analysis method and multiple linear regression model. The grey relational analysis method is used to calculate the correlation degree of energy influencing factors, and then the factors that have more significant impact on energy consumption are selected as the model input variables to establish the tram energy model. The experimental verification shows that the prediction method proposed in this paper can more accurately predict the energy consumption of trams and provide some references for the energy conservation management of trams.
Key concepts: Energy consumption, Grey relational analysis, Regression analysis, Computer science, Energy conservation, Consumption (sociology), Energy (signal processing), Linear regression