• Title/Summary/Keyword: Rank algorithm

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Emergency Service Restoration Algorithm Considering Service Rank in Distribution System (서비스우선순위를 고려한 긴급정전복구 앨고리즘)

  • Song, Kil-Yeong;So, Min-He;Jeong, Min-Hwa;NamKung, Jae-yong
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.800-803
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    • 1996
  • This paper proposes the algorithm to solve emergency service restoration problems using efficient reconfiguration method in distribution system. In this algorithm, we try to avoid the blackout of important loads by considering service rank. It is possible to reconfigurate the system by using fuzzy inference results in which was reflected the expected distribution power, line capacity and service rank. A 27-bus, 32-branch model system is used to demonstrate the effectiveness of the proposed algorithm.

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Importance Assessment of Multiple Microgrids Network Based on Modified PageRank Algorithm

  • Yeonwoo LEE
    • Korean Journal of Artificial Intelligence
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    • v.11 no.2
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    • pp.1-6
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    • 2023
  • This paper presents a comprehensive scheme for assessing the importance of multiple microgrids (MGs) network that includes distributed energy resources (DERs), renewable energy systems (RESs), and energy storage system (ESS) facilities. Due to the uncertainty of severe weather, large-scale cascading failures are inevitable in energy networks. making the assessment of the structural vulnerability of the energy network an attractive research theme. This attention has led to the identification of the importance of measuring energy nodes. In multiple MG networks, the energy nodes are regarded as one MG. This paper presents a modified PageRank algorithm to assess the importance of MGs that include multiple DERs and ESS. With the importance rank order list of the multiple MG networks, the core MG (or node) of power production and consumption can be identified. Identifying such an MG is useful in preventing cascading failures by distributing the concentration on the core node, while increasing the effective link connection of the energy flow and energy trade. This scheme can be applied to identify the most profitable MG in the energy trade market so that the deployment operation of the MG connection can be decided to increase the effectiveness of energy usages. By identifying the important MG nodes in the network, it can help improve the resilience and robustness of the power grid system against large-scale cascading failures and other unexpected events. The proposed algorithm can point out which MG node is important in the MGs power grid network and thus, it could prevent the cascading failure by distributing the important MG node's role to other MG nodes.

Performance Analysis of an Estimated Closeness Centrality Ranking Algorithm in Large-Scale Workflow-supported Social Networks (대규모 워크플로우 소셜 네트워크의 추정 근접 중심도 랭킹 알고리즘 성능 분석)

  • Kim, Jawon;Ahn, Hyun;Kim, Kwanghoon
    • Journal of Internet Computing and Services
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    • v.16 no.3
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    • pp.71-77
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    • 2015
  • This paper implements an estimated closeness centrality ranking algorithm in large-scale workflow-supported social networks and performance analyzes of the algorithm. Existing algorithm has a time complexity problem which is increasing performance time by network size. This problem also causes ranking process in large-scale workflow-supported social networks. To solve such problems, this paper conducts comparison analysis on the existing algorithm and estimated results by applying estimated-driven RankCCWSSN(Rank Closeness Centrality Workflow-supported Social Network). The RankCCWSSN algorithm proved its time-efficiency in a procedure about 50% decrease.

Patent citation network analysis (특허 인용 네트워크 분석)

  • Lee, Minjung;Kim, Yongdai;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.613-625
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    • 2016
  • The development of technology has changed the world drastically. Patent data analysis helps to understand modern technology trends and predict prospective future technology. In this paper, we analyze the patent citation network using the USPTO data between 1985 and 2012 to identify technology trends. We use network centrality measures that include a PageRank algorithm to find core technologies and identify groups of technology with similar properties with statistical network models.

Decoupled Location Parameter Estimation of 3-D Near-Field Sources in a Uniform Circular Array using the Rank Reduction Algorithm

  • Jung, Tae-Jin;Kwon, Bum-Soo;Lee, Kyun-Kyung
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.3
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    • pp.129-135
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    • 2011
  • An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

Improved PageRank Algorithm Using Similarity Information of Documents (문서간의 유사도를 이용한 개선된 PageRank 알고리즘)

  • 이경희;김민구;박승규
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.169-171
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    • 2003
  • 웹에서의 검색 방법에는 크게 Text-Based 기법과 Link-Based 기법이 있다. 본 논문은 그 중에서 Link-Based 기법의 하나인 PageRank 알고리즘에 대해 연구 하고자 한다. 이 PageRank 알고리즘은 각 페이지의 중요성을 수치로 계산하는 방법이다. 하지만 이 알고리즘에서는 페이지에서 페이지로 링크를 따라갈 확률의 값을 일정하게 주어서 모든 페이지의 값을 획일적으로 계산하였기 때문에 각 페이지의 검색 효율성에 문제가 있다고 판단하여, 이를 해결하고자 본 논문은 페이지사이의 유사도를 측정하여 유사도에 따라 링크를 따라가는 확률 값인 Damping factor값을 다르게 부여하여 검색의 효율성을 높였다. 이를 위하여 두 가지 방법의 실험을 통하여 구현, 증명하였다.

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A Speaker Pruning Method for Real-Time Speaker Identification System

  • Kim, Min-Joung;Suk, Soo-Young;Jeong, Jong-Hyeog
    • IEMEK Journal of Embedded Systems and Applications
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    • v.10 no.2
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    • pp.65-71
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    • 2015
  • It has been known that GMM (Gaussian Mixture Model) based speaker identification systems using ML (Maximum Likelihood) and WMR (Weighting Model Rank) demonstrate very high performances. However, such systems are not so effective under practical environments, in terms of real time processing, because of their high calculation costs. In this paper, we propose a new speaker-pruning algorithm that effectively reduces the calculation cost. In this algorithm, we select 20% of speaker models having higher likelihood with a part of input speech and apply MWMR (Modified Weighted Model Rank) to these selected speaker models to find out identified speaker. To verify the effectiveness of the proposed algorithm, we performed speaker identification experiments using TIMIT database. The proposed method shows more than 60% improvement of reduced processing time than the conventional GMM based system with no pruning, while maintaining the recognition accuracy.

PageRank Algorithm Using Link Context (링크내역을 이용한 페이지점수법 알고리즘)

  • Lee, Woo-Key;Shin, Kwang-Sup;Kang, Suk-Ho
    • Journal of KIISE:Databases
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    • v.33 no.7
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    • pp.708-714
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    • 2006
  • The World Wide Web has become an entrenched global medium for storing and searching information. Most people begin at a Web search engine to find information, but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is Web spamming as Google bombing that is based on the PageRank algorithm, one of the most famous Web structuring techniques. In this paper, we regard the Web as a directed labeled graph that Web pages represent nodes and the corresponding hyperlinks edges. In the present work, we define the label of an edge as having a link context and a similarity measure between link context and the target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. A motivating example is investigated in terms of the Singular Value Decomposition with which our algorithm can outperform to filter the Web spamming pages effectively.

Detecting Intentionally Biased Web Pages In terms of Hypertext Information (하이퍼텍스트 정보 관점에서 의도적으로 왜곡된 웹 페이지의 검출에 관한 연구)

  • Lee Woo Key
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.59-66
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    • 2005
  • The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

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RankBoost Algorithm for Personalized Education of Chinese Characters on Smartphone (스마트폰 상에서의 개인화 학습을 위한 랭크부스트 알고리즘)

  • Kang, Dae-Ki;Chang, Won-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.70-76
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    • 2010
  • In this paper, we propose a personalized Chinese character education system using RankBoost algorithm on a smartphone. In a typical Chinese character education scenario, a trainee is supplied with a finite number of Chinese characters as an input set in the beginning. And, as the training session repeats, the trainee will notice her/his difficult characters in the set which she/he hardly answers. Those characters reflect their personalized degrees of difficulty. Our proposed system constructs these personalized degrees of difficulty using RankBoost algorithm. In the beginning, the algorithm start with the set of Chinese characters, of which each is associated with the same weight values. As the training sessions are repeated, the algorithm increase the weights of Chinese characters that the trainee mistakes, thereby eventually constructs the personalized difficulty degrees of Chinese characters. The proposed algorithm maximizes the educational effects by having the trainee exposed to difficult characters more than easy ones.