• Title/Summary/Keyword: flexible decision algorithm

검색결과 34건 처리시간 0.026초

퍼지 이론을 이용한 핸드오버 알고리즘 (A Handover Algorithm Using Fuzzy Set Theory)

  • 정한호;김준철;이준환
    • 한국통신학회논문지
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    • 제18권6호
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    • pp.824-834
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    • 1993
  • 주파수 이용 효율을 극대화하기 위한 셀룰러 이동 통신 시스템에서는 셀의 반경이 작아지면 이동국이 한 셀내에 잔류하는 시간이 짧아지고, 많은 핸드오버가 발생할 수 있게 된다. 또한 핸드오버 결정에 사용되는 수신 신호 전계 강도와 비트 에러율, 기지국과 이동국과의 거리 등의 파라미터는 부정확하게 측정되고 단일 파라메터에 의해 핸드오버 결정은 불충분하기 때문에, 측정치들을 함께 고려하여 핸드오버 결정을 강인하고 유연하게 할 수 있는 알고리즘을 필요로 한다. 본 논문에서는 퍼지 이론을 이용한 다기준(multi-criteria) 의사 결정 문제로 부정확한 다수의 파라미터를 이용하는 핸드오버 알고리즘을 제안하였는데 모의 실험 결과에 따르면 이 알고리즘을 쓸 경우 전체적인 의사 결정이 신뢰성이 있으며 유연하게 되었다. 제안된 알고리즘은 호 중단율, 핸드오버 요청율등의 평가 파라미터를 이용하여 전계 강도만을 이용하는 방법들과 비교되었다.

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An Optimization Algorithm with Novel Flexible Grid: Applications to Parameter Decision in LS-SVM

  • Gao, Weishang;Shao, Cheng;Gao, Qin
    • Journal of Computing Science and Engineering
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    • 제9권2호
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    • pp.39-50
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    • 2015
  • Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

Reliability-Based Iterative Proportionality-logic Decoding of LDPC Codes with Adaptive Decision

  • Sun, Youming;Chen, Haiqiang;Li, Xiangcheng;Luo, Lingshan;Qin, Tuanfa
    • Journal of Communications and Networks
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    • 제17권3호
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    • pp.213-220
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    • 2015
  • In this paper, we present a reliability-based iterative proportionality-logic decoding algorithm for two classes of structured low-density parity-check (LDPC) codes. The main contributions of this paper include: 1) Syndrome messages instead of extrinsic messages are processed and exchanged between variable nodes and check nodes, which can reduce the decoding complexity; 2) a more flexible decision mechanism is developed in which the decision threshold can be self-adjusted during the iterative process. Such decision mechanism is particularly effective for decoding the majority-logic decodable codes; 3) only part of the variable nodes satisfying the pre-designed criterion are involved for the presented algorithm, which is in the proportionality-logic sense and can further reduce the computational complexity. Simulation results show that, when combined with factor correction techniques and appropriate proportionality parameter, the presented algorithm performs well and can achieve fast decoding convergence rate while maintaining relative low decoding complexity, especially for small quantized levels (3-4 bits). The presented algorithm provides a candidate for those application scenarios where the memory load and the energy consumption are extremely constrained.

조합 유전 알고리듬을 이용한 항공기 엔진 시스템의 최적설계 (Optimal Design of Aircraft Gas Turbine System supported by Squeeze Film Damper Using Combined Genetic Algorithm)

  • 김영찬;안영공;양보석;길병래
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 춘계학술대회논문집
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    • pp.514-519
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    • 2003
  • The aircraft engine is usually supported by rolling element bearings and has a small damping rate, which is vol y sensitive to external force. The high-performance requirement of the rotors leads to complex assembly designs and are more flexible. Squeeze film dampers (SFDs) are introduced to provide damping while crossing the critical speeds and stability to the rotor s :stem. Hence, the focus of the present investigation is on the decision of an optimal size of the flexible rotor system supported by the squeeze film dampers to minimize the maximum transmitted load and unbalance response over a range operating speeds. The enhanced genetic algorithm (EGA), which was developed by authors, is used in the optimization process. This algorithm is based on the synthesis of a modified genetic algorithm and simplex method. The results show significant benefits in using EGA when compared with nonlinear programming (NLP).

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AGV시스템에서 적응 규칙을 갖는 퍼지 급송알고리듬에 관한 연구 (A Fuzzy Dispatching Algorithm with Adaptive Control Rule for Automated Guided Vehicle System in Job Shop Environment)

  • 김대범
    • 한국시뮬레이션학회논문지
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    • 제9권1호
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    • pp.21-38
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    • 2000
  • A fuzzy dispatching algorithm with adaptable control scheme is proposed for more flexible and adaptable operation of AGV system. The basic idea of the algorithm is prioritization of all move requests based on the fuzzy urgency. The fuzzy urgency is measured by the fuzzy multi-criteria decision-making method, utilizing the relevant information such as incoming and outgoing buffer status, elapsed time of move request, and AGV traveling distance. At every dispatching decision point, the algorithm prioritizes all move requests based on the fuzzy urgency. The performance of the proposed algorithm is compared with several dispatching algorithms in terms of system throughput in a hypothetical job shop environment. Simulation experiments are carried out varying the level of criticality ratio of AGVs , the numbers of AGVs, and the buffer capacities. The rule presented in this study appears to be more effective for dispatching AGVs than the other rules.

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탐색 알고리즘을 이용한 냉간 단조 공정 설계 (Multi-Stage Cold Forging Process Design with A* Searching Algorithm)

  • 김홍석;임용택
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 1995년도 추계학술대회논문집
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    • pp.30-36
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    • 1995
  • Conventionally design for multi-stage cold forging depends on the designer's experience and decision-making. Due to such non-deterministic nature of the process sequence design, a flexible inference engine is needed for process design expert system. In this study, A* searching algorithm was introduced to arrive at the vetter process sequence design considering the number of forming stages and levels of effective strain, effective stress, and forming load during the porcess. In order to optimize the process sequence in producing the final part, cost function was defined and minimized using the proposed A* searching algorithm. For verification of the designed forming sequences, forming experiments and finite element analyses were carried out in the present investigation. The developed expert system using A* searching algorithm can produce a flexible design system based on changes in the number of forming stages and weights.

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시설 재배용 실내 환경 제어를 위한 역전파 알고리즘 적용 (Implementation of Backpropagation Algorithm For Flexible Factory Environment Control)

  • 공휘식
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2006년도 하계종합학술대회
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    • pp.833-834
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    • 2006
  • In this paper, It is proposed collecting, processing, and learning of data with PIC16F877 and Acode 300[3], constructing database in PC. The PIC16F877 microcontroller nodes are the radio sensor and the DC motor controller. The PC of flexible factory level construct the data-table for object-oriented optimal environment control. The DC Motor control command is decision with back-propagation.

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Reinforcement Learning-Based Intelligent Decision-Making for Communication Parameters

  • Xie, Xia.;Dou, Zheng;Zhang, Yabin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권9호
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    • pp.2942-2960
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    • 2022
  • The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

HEVC 인트라 코딩을 위한 모멘트 기반 고속 CU크기 결정 방법 (Moment-based Fast CU Size Decision Algorithm for HEVC Intra Coding)

  • 김유선;이시웅
    • 한국콘텐츠학회논문지
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    • 제16권10호
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    • pp.514-521
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    • 2016
  • HEVC 비디오 압축 표준은 기존 비디오 표준보다 더 다양한 블록 구조와 예측 모드를 사용함으로써 우수한 부호화 성능을 제공하나, 최적의 블록 크기 및 예측 모드를 결정하기 위한 RDO(Rate Distortion Optimization)과정으로 인해 연산량이 많다는 단점을 가진다. 이를 개선하기 위해 본 논문에서는 화면 내 예측 수행 전 CU영역의 모멘트 값을 계산하고 이를 CU영역의 텍스쳐 복잡도로 이용하여 CU의 분할 여부를 결정하는 모멘트 기반의 고속 CU크기 결정 방법을 제안한다. 제안하는 방법은 기존의 방법을 차용하여 CU영역의 밝기 값에 대한 분산 값을 계산하여 영역의 텍스쳐 평평도를 추정하고, 추가로 CU영역의 밝기 값에 대한 비대칭도를 계산하여 CU영역을 이루는 밝기 값 분포의 비대칭성 정도를 측정한 뒤 이를 조합하여 기존 방법보다 더 정밀하게 텍스쳐 복잡도를 측정하였으며, 이를 RDO과정 중 현재 CU의 분할 여부를 결정하는데 이용하여 기존의 부정확한 CU분할 여부 결정 방법을 개선시킨 고속 CU크기 결정 방법을 제안한다. 제안 방법의 실험 결과는 기존 방법 대비 4.2%의 BD-rate 감소를 보여주며, HM-10.0과 비교하여 BD-rate는 1.1% 증가하였고, 인코딩 시간이 32% 절감되었다.

가변 그룹 유전자알고리즘 기반의 시험자원할당 문제 해결 (Solving the test resource allocation using variable group genetic algorithm)

  • 문창민
    • 한국정보통신학회논문지
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    • 제20권8호
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    • pp.1415-1421
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    • 2016
  • 무기체계의 기능 및 성능 검증을 위한 시험들이 지속적으로 증가함에 따라 가용 자원들의 효율적인 활용을 위한 방안에 관련된 연구가 대두되고 있으며, 자원할당 복잡도가 증가함에 따라 시험계획 시에 의사결정 지원이 요구되고 있다. 시험자원할당은 전통적인 FJSP(Flexible Job Shop Problem)와 기본적으로 동일한 문제이며, 이는 NP-hard문제로서 기존의 경험기반 시험자원 할당 방법으로는 시간 효율적인 자원할당에 있어서 한계가 존재한다. FJSP에 유전자알고리즘을 적용한 최적해 탐색 연구가 진행되어 왔지만, 하나의 기계조작에 대해 두 개 이상 기계의 동시 작동이 필요한 시험자원할당 도메인에서의 적용은 제한적이다. 이에 본 논문에서는 가변 그룹 유전자알고리즘을 제안한다. 제안하는 알고리즘은 수작업 기반의 기존 시험자원할당을 자동화하고 최적화함으로써 시험 효율을 향상시킬 것으로 기대되며, MATLAB을 이용한 시뮬레이션을 통해 그 적용성을 확인하였다.