An Investigation on Feature Extraction and Feature Selection for Power Quality Classification with High Resolution and RMS Data

2021 ◽  
Author(s):  
Adrian Eisenmann ◽  
Tim Streubel ◽  
Krzysztof Rudion
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
High Resolution ◽  
Power Quality ◽  
Quality Classification ◽  
Selection For

ANOVA Based Feature Analysis and Selection in Power Quality Disturbances Identification

2015 ◽  
Vol 793 ◽  
pp. 510-515
Author(s):  
Kamarulazhar Daud ◽  
Ahmad Farid Abidin ◽  
Harapajan Singh Nagindar Singh
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Power Quality ◽  
Feature Analysis ◽  
New Approach ◽  
S Transform ◽  
Different Types ◽  
Power Quality Disturbances ◽  
Selection For ◽  
Windowing Technique

This study was conducted in order to identify the different types of PQD based on a new approach the Analysis Of Variance (ANOVA). ANOVA is used as feature selection for the Power Quality Disturbances (PQD) parameters. The datum of PQD from the PSCAD/EMTDC® simulation has been validated before feature extraction analysis can be commenced. The obtained datum is then analyzed by using cycle windowing technique based on Continuous S-Transform (CST) to extract the features and its characteristics. Moreover, the study focuses an important issue concerning the identification of PQD selection and detection. The feature and characteristics of four types of signal such as Sag, Swell, Transient and sinusoidal normal signal are obtained. The outcome of the analysis shows that a new approach ANOVA have a different result in term of identification of PQD.

Object-based feature selection for crop classification using multi-temporal high-resolution imagery

2018 ◽  
Vol 40 (5-6) ◽  
pp. 2053-2068 ◽  
Author(s):  
Qian Song ◽  
Mingtao Xiang ◽  
Ciara Hovis ◽  
Qingbo Zhou ◽  
Miao Lu ◽  
...  
Keyword(s):  
Feature Selection ◽  
High Resolution ◽  
High Resolution Imagery ◽  
Object Based ◽  
Multi Temporal ◽  
Selection For ◽  
Crop Classification

Feature extraction and feature selection for classifying cyber traffic threats

2016 ◽  
Vol 14 (3) ◽  
pp. 217-231
Author(s):  
Kristy L Moore ◽  
Trevor J Bihl ◽  
Kenneth W Bauer ◽  
Thomas E Dube
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Selection For
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