Open AccessPrediction of the Number of Pure Electric Vehicles Based on the Extended GM(1,1) Model
Author(s) -
Xianfeng Song,
Yulu Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1885/4/042029
Subject(s) - matlab , gray (unit) , statistics , series (stratigraphy) , mean squared prediction error , mean squared error , econometrics , mathematics , computer science , biology , medicine , paleontology , radiology , operating system
The gray system theory is used to study the changes in the number of pure electric vehicles nationwide. According to the data on the number of pure electric vehicles in the country from 2016 to 2020, the original time series prediction model is established based on the GM(1,1) model. Using MATLAB to establish the original GM(1,1), new information GM(1,1) and metabolic GM(1,1), and compare them, and select the metabolic GM(1,1) with the smallest sum of squared errors for model performance Inspection and error analysis showed that the degree of fit was up to standard, and the predicted results were obtained. The prediction results show that the number of pure electric vehicles in my country will increase year by year from 2021 to 2023, and the number of pure electric vehicles in my country will exceed 10 million by the end of 2023.