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- W3130331379 abstract "This chapter takes train manual driving, automatic driving, and unmanned driving as the research object, and introduces the commonly used data mining and processing technologies. The application methods of data mining technology under different driving modes are compared and analyzed. Based on this idea, this chapter is divided into three sections, namely data mining and processing technology of manual driving mode, data mining and processing technology of automatic driving mode, and data mining and processing technology of unmanned driving mode. In each section, the relevant data types are first introduced. Then the existing data mining technologies are summarized and analyzed. In this chapter, the existing data mining and processing technologies are divided into four categories, namely the clustering algorithm, the ensemble algorithm, classification methods, and machine learning methods, and several typical algorithm models of these methods are introduced. For example, the bagging algorithm in the ensemble algorithm, the random forest algorithm in the classification method, the BP neural network in the machine learning algorithm, and so on. Besides, the data processing processes under different driving modes are also compared and analyzed horizontally. This chapter makes a comprehensive introduction to the data mining technology used under the unmanned driving mode by comparing the three models with each other." @default.
- W3130331379 created "2021-03-01" @default.
- W3130331379 creator A5070606018 @default.
- W3130331379 date "2021-01-01" @default.
- W3130331379 modified "2023-09-23" @default.
- W3130331379 title "Data mining and processing for train unmanned driving systems" @default.
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- W3130331379 doi "https://doi.org/10.1016/b978-0-12-822830-2.00005-2" @default.
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