Research on vehicle fuel consumption prediction model based on Cauchy mutation multiverse algorithm

被引:1
作者
Chen, Chenxi [1 ]
Liu, Quan [1 ]
Chen, Qiyuan [1 ]
Yan, Junwei [1 ]
机构
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan, Peoples R China
来源
2022 9TH INTERNATIONAL FORUM ON ELECTRICAL ENGINEERING AND AUTOMATION, IFEEA | 2022年
关键词
Fuel consumption prediction; CMVO; Tangent descent factor;
D O I
10.1109/IFEEA57288.2022.10038213
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The establishment of a truck fuel consumption prediction model is helpful to improve fuel economy and reduce carbon emissions to protect the environment. In the plateau environment, complex geographical conditions have a dramatic impact on fuel consumption. Traditional fuel consumption models can not meet the requirements of plateau prediction accuracy and robustness. In this paper, a back propagation fuel consumption prediction model based on the Cauchy Multi-Verse Optimizer (CMVO) considering plateau conditions is proposed. A Cauchy factor is introduced to improve the global search ability of MVO. Moreover, a tangent descent factor is introduced to reconstruct its travel distance rate (TDR), which significantly improves the convergence speed of algorithm. The experimental results show that the convergence time of CMVO-BP is 50% shorter than that of MVO-BP; Compared with logistic regression and RNN algorithm, the prediction accuracy is improved by 5.7%. Under the plateau high-speed condition, the accuracy of fuel consumption prediction can reach 97.5%, R-2 coefficient score can reach 95.7.
引用
收藏
页码:1115 / 1119
页数:5
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