Regional Voltage Stability Prediction Based on Decision Tree Algorithm

2015 ◽  
Author(s):  
Teng Yun ◽  
Huo Tengyu ◽  
Liu Bing ◽  
Tang Jing ◽  
Zhang Zhongjie
Keyword(s):  
Decision Tree ◽  
Voltage Stability ◽  
Stability Prediction ◽  
Decision Tree Algorithm ◽  
Tree Algorithm

scholarly journals Developing a Decision Tree Algorithm for Wind Power Plants Siting and Sizing in Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2293
Author(s):  
Santosh Ghimire ◽  
Seyed Morteza Alizadeh
Keyword(s):  
Decision Tree ◽  
Wind Power ◽  
Power Plants ◽  
Voltage Stability ◽  
Distribution Networks ◽  
Stability Criteria ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
Wind Power Plants ◽  
Proposed Model

The interconnection of wind power plants (WPPs) with distribution networks has posed many challenges concerned with voltage stability at the point of common coupling (PCC). In a distribution network connected WPP, the short-circuit ratio (SCR) and impedance angle ratio seen at PCC (X/RPCC) are the most important parameters, which affect the PCC voltage (VPCC) stability. Hence, design engineers need to conduct the WPP siting and sizing assessment considering the SCR and X/RPCC seen at each potential PCC site to ensure that the voltage stability requirements defined by grid codes are provided. In various literature works, optimal siting and sizing of distributed generation in distribution networks (DG) has been carried out using analytical, numerical, and heuristics approaches. The majority of these methods require performing computational tasks or simulate the whole distribution network, which is complex and time-consuming. In addition, other works proposed to simplify the WPP siting and sizing have limited accuracy. To address the aforementioned issues, in this paper, a decision tree algorithm-based model was developed for WPP siting and sizing in distribution networks. The proposed model eliminates the need to simulate the whole system and provides a higher accuracy compared to the similar previous works. For this purpose, the model accurately predicts key voltage stability criteria at a given interconnection point, including VPCC profile and maximum permissible wind power generation, using the SCR and X/RPCC values seen at that point. The results confirmed the proposed model provides a noticeable high accuracy in predicting the voltage stability criteria under various validation scenarios considered.

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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