An Explicit Decision Tree Approach for Automated Driving

2017 ◽  
Author(s):  
Nan Li ◽  
Hao Chen ◽  
Ilya Kolmanovsky ◽  
Anouck Girard
Keyword(s):  
Markov Chain ◽  
Decision Tree ◽  
Discrete Time ◽  
Decision Tree Algorithm ◽  
Automated Driving ◽  
Discrete Time Markov Chain ◽  
Tree Algorithm ◽  
Simulation Results ◽  
Partially Observable ◽  
Tree Approach

In this paper, an explicit decision tree approach for automated driving is proposed. The ego vehicle operates in traffic that is modeled as a discrete-time Markov chain, the state of which is only partially observable. In this setting, the automated driving policy is generated from a decision tree algorithm offline operation to create an explicit implementation for the online use. Simulation results of an implementation of this approach for automated driving on a two-lane highway are reported to illustrate the potential of this approach.

scholarly journals Classification of diabetes disease using decision tree algorithm (C4.5)

2021 ◽  
Vol 1869 (1) ◽  
pp. 012082
Author(s):  
B A C Permana ◽  
R Ahmad ◽  
H Bahtiar ◽  
A Sudianto ◽  
I Gunawan
Keyword(s):  
Decision Tree ◽  
Decision Tree Algorithm ◽  
Tree Algorithm

An Analysis of Factors Influencing Foreign Language Self-Efficacy Based on C5.0 Decision Tree Algorithm in Data Mining

2014 ◽  
Vol 538 ◽  
pp. 460-464
Author(s):  
Xue Li
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Foreign Language ◽  
Language Learning ◽  
Learning Strategies ◽  
Self Efficacy ◽  
Foreign Language Learning ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C5.0 Decision Tree

Based on inter-correlation and permeability among disciplines, the author makes an attempt to apply the information science to cognitive linguistics to provide a new perspective for the study of foreign languages. The correlation between self-efficacy and such four factors as anxiety, learning strategies, motivation and learners’ past achievement is analyzed by means of data mining and the extent to which the above factors affect self-efficacy in language learning is explored in this paper. The paper employs the decision tree algorithm in SPSS Clementine. C5.0 decision tree algorithm is adopted to analyze data in the study. The results are elicited from the researches carried out in this paper. The increased anxiety is bound to weaken learners’ motivation over time. It is obvious that learners have low self-efficacy. It is very important to employ strategies in foreign language learning. Ignorance of using learning strategies may result in unplanned learning with unsatisfactory achievements in spite of more efforts involved. Self-efficacy in foreign language learning may be weakened accordingly. Learners’ past achievement is a reference dimension in measuring self-efficacy with weaker influence.

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