Title
Dimensional Reduction on an Intelligent Model for Efficiency Improvement of Switching Modes Detection
Abstract
This research implements a dimensional reduction with the aim of improving the efficiency of a classification algorithm used for detection of different operation modes of a buck converter. The analysis of a half-bridge buck converter is done showing two different working state: hard-switching and soft-switching. A model for dimensional reduction is used on the input data of a classification model. The dimensional reduction helps to reduce the computational costs and improve the performance of the classification model. Very good results were obtained and an improve in the classification accuracy is achieved.
Year
DOI
Venue
2021
10.1007/978-3-030-87869-6_2
16TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS (SOCO 2021)
Keywords
DocType
Volume
Hard-switching, Soft-switching, Half-bridge, Buck converter, Power electronics, Classification, Dimensional reduction
Conference
1401
ISSN
Citations 
PageRank 
2194-5357
0
0.34
References 
Authors
0
5