Abstract
A reasonable design of the operating condition curve of automobile running state is conducive to improving the credibility of the government, so it is more and more important to formulate a test condition that reflects the actual road driving conditions in China. The actual fuel consumption is very different from the regulatory certification results. In order to construct the model mainly by two-segment clustering, the initial clustering of the processed data is carried out by self-organizing mapping neural network, and the cluster number and clustering center are obtained to solve the problem of poor convergence in the K-means model in the early stage. In view of the construction of the operating condition curve of the driving characteristics of light vehicles in a city, the data pre-processing, the extraction of motion fragments and the construction of the driving conditions of a car are to be provided for the driving data set of the same vehicle in a city.
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Acknowledgments
1. Major special project of science and technology of Guangdong Province, No: 190826175545233.
2. Beijing science and technology innovation service capability construction project (PXM2016_014223_000025).
3. BIGC Project(Ec202007).
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Yan, J., Guan, X., Zeng, Q., Zhou, C., Li, Y., You, F. (2021). An Analysis Model of Automobile Running State Based on Neural Network. In: Weng, Y., Yin, Y., Kuang, L., Zhang, Z. (eds) Tools for Design, Implementation and Verification of Emerging Information Technologies. TridentCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 380. Springer, Cham. https://doi.org/10.1007/978-3-030-77428-8_7
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DOI: https://doi.org/10.1007/978-3-030-77428-8_7
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