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RISS 인기검색어
- 검색키워드
- 저자 : Wenbo Kang (검색결과 4 건)
- 무료
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- 유료
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Research on Line Overload Emergency Control Strategy Based on the Source-Load Synergy Coefficient
Jing Ma,Wenbo Kang,James S. Thorp 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.3
A line overload emergency control strategy based on the source-load synergy coefficient is proposed in this paper. First, the definition of the source-load synergy coefficient is introduced. When line overload is detected, the source-load branch synergy coefficient and source-load distribution synergy coefficient are calculated according to the real-time operation mode of the system. Second, the generator tripping and load shedding control node set is determined according to the source-load branch synergy coefficient. And then, according to the line overload condition, the control quantity of each control node is determined using the Double Fitness Particle Swarm Optimization (DFPSO), with minimum system economic loss as the objective function. Thus load shedding for the overloaded line could be realized. On this basis, in order to guarantee continuous and reliable power supply, on the condition that no new line overload is caused, some of the untripped generators are selected according to the source-load distribution synergy coefficient to increase power output. Thus power supply could be restored to some of the shedded loads, and the economic loss caused by emergency control could be minimized. Simulation tests on the IEEE 10-machine 39-bus system verify the effectiveness and feasibility of the proposed strategy.
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Research on Line Overload Emergency Control Strategy Based on the Source-Load Synergy Coefficient
Ma, Jing,Kang, Wenbo,Thorp, James S. The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.3
A line overload emergency control strategy based on the source-load synergy coefficient is proposed in this paper. First, the definition of the source-load synergy coefficient is introduced. When line overload is detected, the source-load branch synergy coefficient and source-load distribution synergy coefficient are calculated according to the real-time operation mode of the system. Second, the generator tripping and load shedding control node set is determined according to the source-load branch synergy coefficient. And then, according to the line overload condition, the control quantity of each control node is determined using the Double Fitness Particle Swarm Optimization (DFPSO), with minimum system economic loss as the objective function. Thus load shedding for the overloaded line could be realized. On this basis, in order to guarantee continuous and reliable power supply, on the condition that no new line overload is caused, some of the untripped generators are selected according to the source-load distribution synergy coefficient to increase power output. Thus power supply could be restored to some of the shedded loads, and the economic loss caused by emergency control could be minimized. Simulation tests on the IEEE 10-machine 39-bus system verify the effectiveness and feasibility of the proposed strategy.
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송신자 자가인증 기법 기반의 스팸 SMS 필터링 안드로이드 애플리케이션 구현
양인식(Inshik Yang),추문박(Wenbo Zou),백전성(Jeanseong Baik),강경태(Kyungtae Kang) 한국컴퓨터정보학회 2018 한국컴퓨터정보학회 학술발표논문집 Vol.26 No.2
스팸·스미싱 SMS의 차단을 위하여 지금까지 다양한 차단기법이 개발되어 사용되고 있다. 그 중에서도 대부분을 차지하는 방법들이 기계학습을 통한 내용 기반의 차단과 사용자의 스팸신고를 통한 송신자 차단 방법이다. 그러나 이러한 방법들은 공통적으로 스팸·스미싱을 식별하기 위해 학습 데이터가 필요하다는 문제점을 갖고 있기 때문에, 신종 스팸 공격들은 차단이 불가능하여 차단율의 한계를 보인다. 본 논문에서는 오늘날 사용되고 있는 스팸·스미싱 차단 기법들의 근본적인 문제점들을 규명하고, 이를 해결할 수 있는 스팸차단 기법 중 하나인 송신자 자가인증 기법을 소개한다. 그리고 송신자 자가인증 기법을 적용한 안드로이드 애플리케이션의 구현 및 동작과정을 설명한다.
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FAFS: A Fuzzy Association Feature Selection Method for Network Malicious Traffic Detection
( Yongxin Feng ),( Yingyun Kang ),( Hao Zhang ),( Wenbo Zhang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.1
Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the de-tection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be signifi-cantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.
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