• Title/Summary/Keyword: step length selection algorithm

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The Improvement of Continuation Power Flow System Including the Algorithm of Practical Step Length Selection (실용적인 스텝크기 선택 알고리듬을 고려한 연속조류계산 시스템의 개발)

  • Song, Hwa-Chang;Lee, Byong-Jun;Kwon, Se-Hyuk
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.3
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    • pp.190-196
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    • 1999
  • Continuation power flow has been developed to remove the ill-condition problem caused by singularity of power flow Jacobian at and near at steady-state voltage instability point in conventional power flow. Continuation power flow consists of predictor and corrector. In prddictor, the direction vector at the resent solution is caluculated and the initial guess of next solution is determined at the distance of step length. The selection of step length is a very important part, since computational speed and convergence performance are both greatly affected by the choice of the step length. This paper presents the practical step length selection algorithm using the reactive power generation sensitivith. In numulation, the proposed algorithm is compared with step length selection algorithm using TVI(tangent vector index).

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Minimum Row Weight and Polar Spectrum Based Puncture Polar Codes Construction Algorithm

  • Liu Daofu;Guo Rui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2157-2169
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    • 2023
  • In order to handle the problem that puncture patterns will change the position distribution of original information bits and frozen bits in polar codes, which affects performance of puncture polar codes further, a minimum row weight and polar spectrum based puncture polar codes construction algorithm (called PA-MRWP) is proposed in this paper. The algorithm calculates row weight of generator matrix and sorts the row weight in ascending order first. Next, the positions with the minimum row weight are selected as initial puncture positions. If the rows with the same row weight cannot all be punctured, polar spectrum based auxiliary puncture scheme is used. In sub-channels with the same row weight, rows corresponding to the polarized sub-channels with higher reliability are selected as puncture positions to construct puncture vector, and the reliability is calculated based on polar spectrum. It is actually a two-step selection strategy, the proposed minimum row weight puncture (MRWP) algorithm is used for primary selection and polar spectrum based auxiliary puncture is used for adjustment. Simulation results show that, compared with worst quality puncture (WQP) algorithm, the proposed PA-MRWP algorithm and Gaussian approximation-aided minimum row weight puncture (GA-MRWP) algorithm provide gains of about 0.46 dB and 0.29 dB at bit error rate (BER) of 10-4, respectively when code length N=400, code rate R=1/2. In addition, the proposed puncture algorithms improve the BER performance significantly with respect to quasi-uniform puncture (QUP) algorithm.

Adaptive Selection of Fast Block Matching Algorithms for Efficient Motion Estimation (효율적인 움직임 추정을 위한 고속 블록 정합 알고리듬의 적응적 선택)

  • Kim, Jung-Jun;Jeon, Gwang-Gil;Jeong, Je-Chang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1C
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    • pp.19-33
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    • 2008
  • A method that is adaptively selecting among previous fast motion estimation algorithms and a newly proposed fast motion estimation algorithm(UCDS) is presented in this paper. The algorithm named AUDC and a newly proposed fast motion estimation algorithms are based on the Diamond Search(DS) algorithm and Three Step Search(TSS). Although many previous fast motion estimation algorithms have lots of advantages, those have lots of disadvantages. So we thought better adaptive selection of fast motion estimation algorithms than only using one fast motion estimation algorithm. Therefore, we propose AUDC that is using length of the MV, Search Point, SAD of the neighboring block and adaptively selecting among Cross Three Step Search(CTSS), Diamond Search(DS) and Ungraded Cross Diamond Search(UCDS). Experimental results show that the AUDC is much more robust, provides a faster searching speed, and smaller distortions than other popular fast block-matching at algorithms.

A Study on DEA-based Stepwise Benchmarking Target Selection Considering Resource Improvement Preferences (DEA 기반의 자원 개선 선호도를 고려한 단계적 벤치마킹 대상 탐색 연구)

  • Park, Jaehun;Sung, Si-Il
    • Journal of Korean Society for Quality Management
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    • v.47 no.1
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    • pp.33-46
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    • 2019
  • Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.