• Title/Summary/Keyword: Energy Minimization algorithm

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다중표적추적의 최적 데이터결합을 위한 MAP 추정기 개발 (A MAP Estimate of Optimal Data Association in Multi-Target Tracking)

  • 이양원
    • 제어로봇시스템학회논문지
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    • 제9권3호
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    • pp.210-217
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    • 2003
  • We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

역방향 CDMA 시스템에서 에너지 최적화된 전송기법: 그래프 이론적 접근 (Energy Optimized Transmission Strategy in CDMA Reverse Link: Graph Theoretic Approach)

  • 오창윤
    • 전자공학회논문지
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    • 제52권6호
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    • pp.3-9
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    • 2015
  • 본 논문에서는 짧은 지연시간을 요구하는 CDMA 시스템 환경에서 전송률 스케줄링과 전력량 할당 문제를 연구한다. 구체적으로, 본 논문은 각각의 단말이 짧은 구간 동안의 평균 전송률을 유지하는 동시에 에너지 효율적인 스케줄링 방안을 제안한다. 다중 코드를 적용한 CDMA 시스템을 고려하며, 각각의 코드는 가상의 사용자로 해석할 수 있다. 논문의 최종 목적은 전송률 과정에서 소모하는 에너지가 최소화되도록 각각의 시간슬럿에 가상의 사용자를 스케줄링하는 방안을 제안하는 것이다. 주목할만한 점은, 본 논문에서 고려하는 전송률 최적화 문제가 최단 경로 알고리즘으로 해결 가능하다는 점이다. 마지막으로, 본 논문이 제안하는 에너지 최적화 스케줄링 방안을 TDMA 형식의 스케줄링 방안과 성능 비교 분석한다.

에드 혹 네트워크에서 에너지 효율성과 네트워크 수명 연장을 위한 지역적 경로 선택 알고리즘 (Localized Path Selection Algorithm for Energy Efficiency and Prolonging Lifetime in Ad-Hoc Networks)

  • 이주영
    • 한국컴퓨터정보학회논문지
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    • 제15권6호
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    • pp.65-72
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    • 2010
  • 에드 혹 네트워크의 각 무선 단말기는 배터리 기반의 제한된 에너지로 동작하기 때문에 효율적인 에너지 사용에 관한 문제는 아주 중요하다. 시스템 수명을 연장하기 위해서는 단말 노드의 에너지 소비를 균형있게 유도하여 어느 특정 단말기의 에너지가 먼저 고갈되어 통신 단절을 초래하는 상황을 지연시켜야 한다. 또한 단말기 노드의 빈번한 이동 등으로 인해 신뢰성이 낮은 링크는 경로 설정시 고려해야 할 요소이다. 본 논문에서 제안하는 CMLR 방법은 잔여 에너지와 링크 에러율, 전송 소비 에너지를 고려한 새로운 비용 관계식을 이용하여 에너지 사용의 효율성을 증가시킨다. 이 방법은 전송 에너지 소모의 최소화와 노드 수명의 최대화 사이의 값을 절충하여 에너지 효율성을 높이고 균형있는 에너지 소비를 유도하여 네트워크 수명을 연장시키도록 하는 방법이다. 또한, 본 논문에서는 시뮬레이션을 통해 제안하는 CMLR의 성능을 검증하였으며, 네트워크 수명과 경로의 효율성 측면에서 볼 때 기존의 알고리즘보다 우수한 결과를 보여주었다.

Analysis of cable structures through energy minimization

  • Toklu, Yusuf Cengiz;Bekdas, Gebrail;Temur, Rasim
    • Structural Engineering and Mechanics
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    • 제62권6호
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    • pp.749-758
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    • 2017
  • In structural mechanics, traditional analyses methods usually employ matrix operations for obtaining displacement and internal forces of the structure under the external effects, such as distributed loads, earthquake or wind excitations, and temperature changing inter alia. These matrices are derived from the well-known principle of mechanics called minimum potential energy. According to this principle, a system can be in the equilibrium state only in case when the total potential energy of system is minimum. A close examination of the expression of the well-known equilibrium condition for linear problems, $P=K{\Delta}$, where P is the load vector, K is the stiffness matrix and ${\Delta}$ is the displacement vector, it is seen that, basically this principle searches the displacement set (or deformed shape) for a system that minimizes the total potential energy of it. Instead of using mathematical operations used in the conventional methods, with a different formulation, meta-heuristic algorithms can also be used for solving this minimization problem by defining total potential energy as objective function and displacements as design variables. Based on this idea the technique called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) is proposed. The method has been successfully applied for linear and non-linear analyses of trusses and truss-like structures, and the results have shown that the approach is much more successful than conventional methods, especially for analyses of non-linear systems. In this study, the application of TPO/MA, with Harmony Search as the selected meta-heuristic algorithm, to cables net system is presented. The results have shown that the method is robust, powerful and accurate.

Energy Based Multiple Refitting for Skinning

  • Jha, Kailash
    • International Journal of CAD/CAM
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    • 제5권1호
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    • pp.11-18
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    • 2005
  • The traditional method of manipulation of knots and degrees gives poor quality of surface, if compatibility of input curves is not good enough. In this work, a new algorithm of multiple refitting of curves has been developed using minimum energy based formulation to get compatible curves for skinning. The present technique first reduces the number of control points and gives smoother surface for given accuracy and the surface obtained is then skinned by compatible curves. This technique is very useful to reduce data size when a large number of data have to be handled. Energy based technique is suitable for approximating the missing data. The volumetric information can also be obtained from the surface data for analysis.

Reinforcement Learning-based Duty Cycle Interval Control in Wireless Sensor Networks

  • Akter, Shathee;Yoon, Seokhoon
    • International journal of advanced smart convergence
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    • 제7권4호
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    • pp.19-26
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    • 2018
  • One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

유전자 알고리즘을 이용한 영구자석 모터의 고정자 잇날 페어링 및 자석 극호각 설계에 의한 코깅 토오크의 저감 설계 (Minimization of Cogging Torque in Permanent Magnet Motors by Stator Pole Shoe Pairing and Magnet Arc Design using Genetic Algorithm)

  • 엄재부;황건용;황상문
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제51권1호
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    • pp.1-6
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    • 2002
  • Cogging torque is often a principal source of vibration and acoustic noise in high precision spindle motor applications. In this paper, cogging torque is analytically calculated using energy method to show that Fourier spectra of airgap permeance function and airgap MMF function are the most important design parameters to control cogging torque. To control these functions, stator pole shoe pairing and magnet arc design are proposed to minimize cogging torque. As for optimization technique, genetic algorithm is applied to handle trade-off effects of design parameters. Results show that the proposed method can reduce the cogging torque effectively.

효율적인 엘레베이터 운행에 관한 연구 (A study of an efficient operation mode of elevator)

  • 김종삼;박만식;이석규;이달해
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.726-729
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    • 1991
  • This paper proposes a new operation algorithm for elevator by considering both better service for passengers and minimization of energy consumption for elevator operation. The main idea of the proposed operation algorithm is based on the assumption that passengers push the numbered buttons indicating their destination, one of the main differences of proposed operation mode from the conventional one is that the elevator may move to the opposite direction for a few floors according to the rescheduled operational pattern determined by some factors. Some examples by computer simulation show the efficiency of the proposed operation algorithm.

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GPU 에서의 고속 스테레오 정합을 위한 메모리 효율적인 Belief Propagation (Memory-Efficient Belief Propagation for Stereo Matching on GPU)

  • 최영규;윌리엄;박인규
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2012년도 추계학술대회
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    • pp.52-53
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    • 2012
  • Belief propagation (BP) is a commonly used global energy minimization algorithm for solving stereo matching problem in 3D reconstruction. However, it requires large memory bandwidth and data size. In this paper, we propose a novel memory-efficient algorithm of BP in stereo matching on the Graphics Processing Units (GPU). The data size and transfer bandwidth are significantly reduced by storing only a part of the whole message. In order to maintain the accuracy of the matching result, the local messages are reconstructed using shared memory available in GPU. Experimental result shows that there is almost an order of reduction in the global memory consumption, and 21 to 46% saving in memory bandwidth when compared to the conventional algorithm. The implementation result on a recent GPU shows that we can obtain 22.8 times speedup in execution time compared to the execution on CPU.

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Multi-objective path planning for mobile robot in nuclear accident environment based on improved ant colony optimization with modified A*

  • De Zhang;Run Luo;Ye-bo Yin;Shu-liang Zou
    • Nuclear Engineering and Technology
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    • 제55권5호
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    • pp.1838-1854
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    • 2023
  • This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A* (IACO-A*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A* IACO-A* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.