• 제목/요약/키워드: Incremental Algorithm

검색결과 371건 처리시간 0.027초

점진적 스레드 트리를 구성하기 위한 파싱 알고리즘 (A Parsing Algorithm for Constructing Incremental Threaded Tree)

  • 이대식
    • 인터넷정보학회논문지
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    • 제7권4호
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    • pp.91-99
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    • 2006
  • 점진적 파싱 기법은 프로그램의 점진적 구성을 허용하는 언어기반 환경의 중요한 부분이며, 프로그램의 변경된 부분에 대해서만 구문분석을 다시 함으로써 시스템의 성능을 향상 시킨다. 기존의 점진적 파싱은 파싱 정보를 저장하기 위해 스택 자료구조를 사용한다. 본 논문에서는 스택 자료구조를 사용하지 않고 노드 주소로 스레드를 추가하여 스레드 트리 구성 알고리즘을 제안한다. 또한 구성된 스레드 트리를 사용하여 5단계의 점진적 파싱 과정으로 나누어 점진적 스레드 트리 구성 알고리즘을 제안한다.

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효율적인 점진적 LR 파성 알고리즘 (An Efficient Incremental LR Parsing Algorithm)

  • 안희학;유채우;송후봉
    • 전자공학회논문지B
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    • 제31B권4호
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    • pp.9-17
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    • 1994
  • The incremental parsing techniques are essential part of language-based environment which allow incremental construction of programs, as reparsing of modified part of the program alone enhances the system performance. A number of methods and algorithms have been proposed for incremental parsing and for the construction of incremental parsers. The purpose of this paper is to review the earlier incremental parsing algorithms which are too expensive in both time and space, and to present an efficient incremental LR parsing algorithm which is more efficient than the previous ones. In this paper, we generate automatically an extended LR parsing tables which allow the nonterminal symbols as well as terminal symbols for the input, and apply them to our efficient incremental LR parsing algorithm. Using these extended LR parsing tables. we suggest several methods to reduce its memory spaces and parsing steps as well. The algorithms described here were implemented in C language and YACC on a SUN UNIX OS, and were tested with several grammars and strings.

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A New Incremental Learning Algorithm with Probabilistic Weights Using Extended Data Expression

  • Yang, Kwangmo;Kolesnikova, Anastasiya;Lee, Won Don
    • Journal of information and communication convergence engineering
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    • 제11권4호
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    • pp.258-267
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    • 2013
  • New incremental learning algorithm using extended data expression, based on probabilistic compounding, is presented in this paper. Incremental learning algorithm generates an ensemble of weak classifiers and compounds these classifiers to a strong classifier, using a weighted majority voting, to improve classification performance. We introduce new probabilistic weighted majority voting founded on extended data expression. In this case class distribution of the output is used to compound classifiers. UChoo, a decision tree classifier for extended data expression, is used as a base classifier, as it allows obtaining extended output expression that defines class distribution of the output. Extended data expression and UChoo classifier are powerful techniques in classification and rule refinement problem. In this paper extended data expression is applied to obtain probabilistic results with probabilistic majority voting. To show performance advantages, new algorithm is compared with Learn++, an incremental ensemble-based algorithm.

계층적 속성문법을 위한 효율적인 점진적 속성평가 (Effective incremental attribute evaluation for a hierarchical attribute grammar)

  • 장재춘;김태훈
    • 인터넷정보학회논문지
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    • 제2권3호
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    • pp.71-79
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    • 2001
  • 점진적 속성 평가 알고리즘에서는 새로운 입력 트리가 기존 입력 트리와 정확히 비교되어서 새로운 트리를 구성할 때 기존 속성 트리의 어떤 서브 트리를 사용해야 하는가를 결정한다. 이 논문에서는 계층적 속성 문법의 점진적 평가를 효율적으로 하기 위해 점진적 속성 평가 알고리즘을 이용하였으며 Carle과 Pollock의 알고리즘을 분석하여 점진적 속성 평가 알고리즘으로 재구성하고, 속성 트리 dcopy의 구성요소를 새로운 속성 트리 d'copy에 적용하여 최적화된 속성 트리 d'copy의 점진적 속성 평가 알고리즘을 구성하였다. 또한 점진적 속성 평가 알고리즘을 이용하여 실제적인 입력 프로그램에서 재사용된 노드의 표현과 정의된 변수 형(type)이 어떻게 점진적인 속성 평가를 수행하는가를 나타내었다.

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Distributed Incremental Approximate Frequent Itemset Mining Using MapReduce

  • Mohsin Shaikh;Irfan Ali Tunio;Syed Muhammad Shehram Shah;Fareesa Khan Sohu;Abdul Aziz;Ahmad Ali
    • International Journal of Computer Science & Network Security
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    • 제23권5호
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    • pp.207-211
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    • 2023
  • Traditional methods for datamining typically assume that the data is small, centralized, memory resident and static. But this assumption is no longer acceptable, because datasets are growing very fast hence becoming huge from time to time. There is fast growing need to manage data with efficient mining algorithms. In such a scenario it is inevitable to carry out data mining in a distributed environment and Frequent Itemset Mining (FIM) is no exception. Thus, the need of an efficient incremental mining algorithm arises. We propose the Distributed Incremental Approximate Frequent Itemset Mining (DIAFIM) which is an incremental FIM algorithm and works on the distributed parallel MapReduce environment. The key contribution of this research is devising an incremental mining algorithm that works on the distributed parallel MapReduce environment.

배전계통의 부하평형을 고려한 고속 계통구성방법 (A Fast Configuration Method for Load Balancing in Distribution System)

  • 남기영;최상봉;정성환;류희석;김호용
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 A
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    • pp.381-383
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    • 2003
  • The authors have developed a solution method based on the incremental algorithm. The optimal load balance between feeders is found through the incremental algorithm with allowing the loop configuration. Therefore loops can be configured in the resulting configuration, and then we must eliminate all loops to satisfy radiality of distribution system because the distribution system is operated under radial status. But the optimal load balance through incremental algorithm is deteriorated when the loops are eliminated. In this paper, authors propose a new method which is to improve the searching procedure of path in the incremental algorithm, that is, so as not to make loop in the path configuration.

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점진적 속성문법을 위한 효과적인 최적화 알고리즘에 관한 연구 (A study on the effectively optimized algorithm for an incremental attribute grammar)

  • 장재춘;안희학
    • 정보처리학회논문지A
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    • 제8A권3호
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    • pp.209-216
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    • 2001
  • 복잡한 언어 처리에 점진적 속성 문법을 적용하기 위해서는 최적화 알고리즘을 사용하는 것이 효과적이다. 점진적 속성문법의 최적화 알고리즘에서는 새로운 입력 속성 트리가 기존 입력 속성 트리와 정확히 비교되어서 새로운 속성 트리를 구성할 대 기존 속성 트리의 어떤 서브트리를 사용해야 하는가를 결정한다. 본 논문에서는 Carle과 Pollock에 의해 제안된 알고리즘을 분석하여 효과적인 최적화 알고리즘으로 재구성하고, 새로은 속성 트리 d'copy의 생성 과정과, 속성트리 d'copy의 새로운 최적화 알고리즘을 추가하였다. 이 논문에서 제안한 매칭 알고리즘의 성능평가를 통하여 기존의 알고리즘 보다 제안한 최적화 알고리즘의 실행 시간을 약 19.5% 향상 시킬 수 있었다.

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IMTAR: Incremental Mining of General Temporal Association Rules

  • Dafa-Alla, Anour F.A.;Shon, Ho-Sun;Saeed, Khalid E.K.;Piao, Minghao;Yun, Un-Il;Cheoi, Kyung-Joo;Ryu, Keun-Ho
    • Journal of Information Processing Systems
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    • 제6권2호
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    • pp.163-176
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    • 2010
  • Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these databases has to be maintained, and an incremental updating technique needs to be developed for maintaining the discovered association rules from these databases. The concept of Temporal Association Rules has been introduced to solve the problem of handling time series by including time expressions into association rules. In this paper we introduce a novel algorithm for Incremental Mining of General Temporal Association Rules (IMTAR) using an extended TFP-tree. The main benefits introduced by our algorithm are that it offers significant advantages in terms of storage and running time and it can handle the problem of mining general temporal association rules in incremental databases by building TFP-trees incrementally. It can be utilized and applied to real life application domains. We demonstrate our algorithm and its advantages in this paper.

실시간 구조물 변위 모니터링을 위한 증분형 변위 측정 알고리즘 (Incremental Displacement Estimation Algorithm for Real-Time Structural Displacement Monitoring)

  • 전해민;신재욱;명완철;명현
    • 제어로봇시스템학회논문지
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    • 제18권6호
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    • pp.579-583
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    • 2012
  • The purpose of this paper is to suggest IDE (Incremental Displacement Estimation) algorithm for the previously proposed visually servoed paired structured light system. The system is composed of two sides facing with each other, each with one or two lasers with a 2-DOF manipulator, a camera, and a screen. The 6-DOF displacement between two sides can be estimated by calculating the positions of the projected laser beams and rotation angles of the manipulators. In the previous study, Newton-Raphson or EKF (Extended Kalman Filter) has been used as an estimation algorithm. Although the various experimental tests have validated the performance of the system and estimation algorithms, the computation time is relatively long since aforementioned algorithms are iterative methods. Therefore, in this paper, a non-iterative incremental displacement estimation algorithm which updates the previously estimated displacement with a difference of the previous and the current observed data is introduced. To verify the performance of the algorithm, experimental tests have been performed. The results show that the proposed non-iterative algorithm estimates the displacement with the same level of accuracy compared to the EKF with multiple iterations with significantly less computation time.

Sliced-Edge Trace 알고리듬을 이용한 계층적 Incremental DRC 시스템 (A Hierarchical and Incremental DRC System Using Sliced-Edge Trace Algorithm)

  • 문인호;김현정;오성환;황선영
    • 전자공학회논문지A
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    • 제28A권1호
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    • pp.60-73
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    • 1991
  • This paper presents an efficient algorithm for incremental and hierarchical design rule checking of VLSI layouts, and describes the implementation of a layout editor using the proposed algorithm. Tracing the sliced edges divided by the intersection of the edges either ina polygon or in two polygons (Sliced-Edge Trace), the algorithm performs VLSI pattern operations like resizing and other Boolean operations. The algorithm is not only fast enough to check the layouts of full-custom designs in real-time, but is general enough to be used for arbitrarily shaped polygons. The proposed algorithm was employed in developingt a layout editor on engineering workstations running UNIX. The editor has been successfully used for checking, generating and resizing of VLSI layouts.

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