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Research on the Diffusion Model of Electric Vehicle Quantity Considering Individual Choice
by
Chen, Wenhui
, Jia, Chenran
, Ding, Can
in
Attitudes
/ Automobiles, Electric
/ Batteries
/ Consumers
/ Costs
/ discrete selection model
/ Electric power
/ Electric vehicles
/ electric vehicles diffusion
/ Electricity
/ Electricity distribution
/ Gasoline
/ individual choice behavior
/ Neural networks
/ Ownership changes
/ Purchasing
/ Regression analysis
/ social effect
/ Subsidies
/ Utility functions
2023
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Research on the Diffusion Model of Electric Vehicle Quantity Considering Individual Choice
by
Chen, Wenhui
, Jia, Chenran
, Ding, Can
in
Attitudes
/ Automobiles, Electric
/ Batteries
/ Consumers
/ Costs
/ discrete selection model
/ Electric power
/ Electric vehicles
/ electric vehicles diffusion
/ Electricity
/ Electricity distribution
/ Gasoline
/ individual choice behavior
/ Neural networks
/ Ownership changes
/ Purchasing
/ Regression analysis
/ social effect
/ Subsidies
/ Utility functions
2023
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Do you wish to request the book?
Research on the Diffusion Model of Electric Vehicle Quantity Considering Individual Choice
by
Chen, Wenhui
, Jia, Chenran
, Ding, Can
in
Attitudes
/ Automobiles, Electric
/ Batteries
/ Consumers
/ Costs
/ discrete selection model
/ Electric power
/ Electric vehicles
/ electric vehicles diffusion
/ Electricity
/ Electricity distribution
/ Gasoline
/ individual choice behavior
/ Neural networks
/ Ownership changes
/ Purchasing
/ Regression analysis
/ social effect
/ Subsidies
/ Utility functions
2023
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Research on the Diffusion Model of Electric Vehicle Quantity Considering Individual Choice
Journal Article
Research on the Diffusion Model of Electric Vehicle Quantity Considering Individual Choice
2023
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Overview
Regarding the issue of individual purchasing behavior in the rapid growth of electric vehicles, this article studies the diffusion model of electric vehicles considering individual choices and social effects from the perspective of the scale and quantity changes of electric vehicles. First, the neural network was used to predict the charging data of electric vehicles, and the economic effects of purchasing electric vehicles were calculated by combining the purchase cost and government subsidies. Then, the utility function for owners to purchase electric or traditional fuel vehicles was created by considering economic effects, cognitive attitudes, and social effects as factors that individuals need to consider when purchasing electric or traditional fuel vehicles. Finally, the discrete choice model was used to calculate the probability of users choosing to purchase electric or traditional fuel vehicles, and the number of electric vehicles was statistically calculated. Analysis of simulation examples shows that the growth rate of fuel vehicles decreases year by year during the simulation period, and the trend of electric vehicle growth follows an S-curve.
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