Contour refinement by enhanced query-based learning

Shyh Jier Huang; Chuan Chang Hung

Contour refinement by enhanced query-based learning

Shyh Jier Huang
, Chuan Chang Hung

電機工程學系

研究成果: Conference article › 同行評審

1 引文斯高帕斯（Scopus）

摘要

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.

原文	English
頁（從 - 到）	616-619
頁數	4
期刊	Proceedings - IEEE International Symposium on Circuits and Systems
卷	2
出版狀態	Published - 1996 1月 1
事件	Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) - Atlanta, GA, USA 持續時間: 1996 5月 12 → 1996 5月 15

All Science Journal Classification (ASJC) codes

電氣與電子工程

其它文件與鏈接

引用此

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title = "Contour refinement by enhanced query-based learning",

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.",

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year = "1996",

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note = "Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) ; Conference date: 12-05-1996 Through 15-05-1996",

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AU - Huang, Shyh Jier

AU - Hung, Chuan Chang

PY - 1996/1/1

Y1 - 1996/1/1

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0029705079

UR - https://www.scopus.com/pages/publications/0029705079#tab=citedBy

M3 - Conference article

AN - SCOPUS:0029705079

SN - 0271-4310

VL - 2

SP - 616

EP - 619

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4)

Y2 - 12 May 1996 through 15 May 1996

ER -

Contour refinement by enhanced query-based learning

摘要

All Science Journal Classification (ASJC) codes

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