Contour refinement by enhanced query-based learning

Shyh Jier Huang, Chuan Chang Hung

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

An enhanced query-based learning neural network is proposed to refine the contour in this paper. The proposed learning approach provides a classifier at a lower computational cost comparing with the other method. The ambiguous regions in the classification process can be thus easier clarified. The proposed approach has been tested on the refinement of security contours in the assessment of power system operations. Results demonstrate the effectiveness and feasibility of the proposed approach for the applications.

Original languageEnglish
Pages (from-to)616-619
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume2
Publication statusPublished - 1996 Jan 1
EventProceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) - Atlanta, GA, USA
Duration: 1996 May 121996 May 15

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Contour refinement by enhanced query-based learning'. Together they form a unique fingerprint.

Cite this