Abstract
This chapter proposes a qualitative feature selection for motor quality types using Weighted Principal Component Analysis (WPCA) method. The WPCA includes two processes, one is the Procedure-FFV (find the final weights) process and the other is the Procedure-DPC (determine the principal components) process. The input variables of the WPCA are nine original features and the output variables are six qualitative features. Experimental results indicate that the proposed WPCA provides an efficient, simple, and fast method for feature selection on motor’s current waveforms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dash, M., Liu, H.: Feature selection for classification. Intell. Data Anal. 1, 131–156 (1997)
Jolliffe, I.T.: Principal Component Analysis. Springer, New York (1986)
Ren, H., Chang, Y.L.: Feature extraction with modified Fisher’s linear discriminant analysis. Proc. SPIE 5995, 56–62 (2005)
Yue, H.H., Tomoyasu, M.: Weighted principal component analysis and its applications to improve FDC performance. In: International Conference on Decision and Control, ICDC-2004, Bahamas, pp. 4262–4267 (2004)
Yeh, Y.C.: Fuzzy logic method for motor quality types on current waveforms. Measurement 46, 1682–1691 (2013)
Yeh, Y.C., Chu, Y., Chang, W.T.: Cardiac Arrhythmia diagnosis on ECG signals using weighted principal component analysis. In: ICME, pp. 357–362 (2014)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Acknowledgement
The work was supported by the Ministry of Science and Technology of Republic of China under Grant MOST 103-2221-E-231-019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Yeh, YC., Lin, LC., Liu, MC., Chu, TS. (2016). Feature Selection Algorithm for Motor Quality Types Using Weighted Principal Component Analysis. In: Juang, J. (eds) Proceedings of the 3rd International Conference on Intelligent Technologies and Engineering Systems (ICITES2014). Lecture Notes in Electrical Engineering, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-17314-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-17314-6_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-17313-9
Online ISBN: 978-3-319-17314-6
eBook Packages: EngineeringEngineering (R0)