• Title/Summary/Keyword: discrete topology

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A Discrete State-Space Control Scheme for Dynamic Voltage Restorers

  • Lei, He;Lin, Xin-Chun;Xue, Ming-Yu;Kang, Yong
    • Journal of Power Electronics
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    • v.13 no.3
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    • pp.400-408
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    • 2013
  • This paper presents a discrete state-space controller using state feedback control and feed-forward decoupling to provide a desirable control bandwidth and control stability for dynamic voltage restorers (DVR). The paper initially discusses three typical applications of a DVR. The load-side capacitor DVR topology is preferred because of its better filtering capability. The proposed DVR controller offers almost full controllability because of the multi-feedback of state variables, including one-beat delay feedback. Feed-forward decoupling is usually employed to prevent disturbances of the load current and source voltage. Directly obtaining the feed-forward paths of the load current and source voltage in the discrete domain is a complicated process. Fortunately, the full feed-forward decoupling strategy can be easily applied to the discrete state-space controller by means of continuous transformation. Simulation and experimental results from a digital signal processor-based system are included to support theoretical analysis.

STRONG k-DEFORMATION RETRACT AND ITS APPLICATIONS

  • Han, Sang-Eon
    • Journal of the Korean Mathematical Society
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    • v.44 no.6
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    • pp.1479-1503
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    • 2007
  • In this paper, we study a strong k-deformation retract derived from a relative k-homotopy and investigate its properties in relation to both a k-homotopic thinning and the k-fundamental group. Moreover, we show that the k-fundamental group of a wedge product of closed k-curves not k-contractible is a free group by the use of some properties of both a strong k-deformation retract and a digital covering. Finally, we write an algorithm for calculating the k-fundamental group of a dosed k-curve by the use of a k-homotopic thinning.

Multi-objective Topology Optimization of Magneto-Thermal Problem considering Heat Flow Rate (열 유입률을 고려한 자계-열계 다목적 위상최적설계)

  • Shim, Ho-Kyung;Wang, Se-Myung;Moon, Hee-Gon;Hameyer, Kay
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.138-139
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    • 2007
  • This research provides machine designers with some intuition to consider both, magnetic and heat transfer effects. A topological multi-objective function includes magnetic energy and heat inflow rate to the system, which equals to the total heat dissipation by conduction and convection. For the thermal field regarding the heat inflow, introduced as a reaction force, topology design sensitivity is derived by employing discrete equations. The adjoint variable method is used to avoid numerous sensitivity evaluations. As a numerical example, a C-core design excited by winding current demonstrates the strength of the multi-physical approach.

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Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization

  • Tejani, Ghanshyam G.;Savsani, Vimal J.;Patel, Vivek K.;Bureerat, Sujin
    • Advances in Computational Design
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    • v.2 no.4
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    • pp.313-331
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    • 2017
  • In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

A Real Time Traffic Flow Model Based on Deep Learning

  • Zhang, Shuai;Pei, Cai Y.;Liu, Wen Y.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.8
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    • pp.2473-2489
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    • 2022
  • Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

Analysis of HMM Topology Criteria on Discrete HMM and Continuous-Density HMM for Handwriting Recognition (필기 데이터 인식을 위한 이산 HMM과 연속 확률밀도 HMM에서의 HMM구조 최적화 기준 분석)

  • PARK Mi-Na;HA Jin-Young
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.853-855
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    • 2005
  • 은닉 마르코프(HMM)의 HMM의 구조 최적을 위한 모델 선택 방법에 많은 방법들이 연구되어지고 있다. HMM의 구조를 어떻게 최적으로 정해야 하는 가에 대해 HMM의 구조를 체계적인 방법으로 정함과 동시에 변별력의 단점을 개선 할 수 있는 방법으로 Anti-likelihood(ALC1)를 제안하였고 이를 모델 선택 기준인 BIC와의 결합(ALC2)하여 필기 데이터에 대해 실험한 결과 기존의 방법보다 파라미터의 수는 감소되고 인식률이 향상됨을 알 수 있었다. 이를 Discrete HMM에도 적용하여 제안된 ALC2가 HMM 구조를 최적화하는 모델 선택 기준임을 Continuous-Density HMM과 비교하여 실험 검증 한다.

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REMARKS ON DIGITAL HOMOTOPY EQUIVALENCE

  • Han, Sang-Eon
    • Honam Mathematical Journal
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    • v.29 no.1
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    • pp.101-118
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    • 2007
  • The notions of digital k-homotopy equivalence and digital ($k_0,k_1$)-homotopy equivalence were developed in [13, 16]. By the use of the digital k-homotopy equivalence, we can investigate digital k-homotopy equivalent properties of Cartesian products constructed by the minimal simple closed 4- and 8-curves in $\mathbf{Z}^2$.

The Design of Self-Organizing Map Using Pseudo Gaussian Function Network

  • Kim, Byung-Man;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.42.6-42
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    • 2002
  • Kohonen's self organizing feature map (SOFM) converts arbitrary dimensional patterns into one or two dimensional arrays of nodes. Among the many competitive learning algorithms, SOFM proposed by Kohonen is considered to be powerful in the sense that it not only clusters the input pattern adaptively but also organize the output node topologically. SOFM is usually used for a preprocessor or cluster. It can perform dimensional reduction of input patterns and obtain a topology-preserving map that preserves neighborhood relations of the input patterns. The traditional SOFM algorithm[1] is a competitive learning neural network that maps inputs to discrete points that are called nodes on a lattice...

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Reinforcement layout design for deep beam based on BESO of multi-level reinforcement diameter under discrete model

  • Zhang, Hu-zhi;Luo, Peng;Yuan, Jian;Huang, Yao-sen;Liu, Jia-dong
    • Structural Engineering and Mechanics
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    • v.84 no.4
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    • pp.547-560
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    • 2022
  • By presetting various reinforcement diameters in topology optimization with the discrete model finite element analysis, an algorithm of bidirectional evolutionary structural optimization of multi-level reinforcement diameter is presented to obtain the optimal reinforcement topologies which describe the degree of stress of different parts. The results of a comparative study on different reinforcement feasible domain demonstrate that the more angle types of reinforcement are arranged in the initial domain, the higher utilization rate of reinforcement of the optimal topology becomes. According to the nonlinear finite element analysis of some deep beam examples, the ones designed with the optimization results have a certain advantage in ultimate bearing capacity, although their failure modes are greatly affected by the reinforcement feasible domain. Furthermore, the bearing capacity can be improved when constructional reinforcements are added in the subsequent design. However the adding would change the relative magnitude of the bearing capacity between the normal and inclined section, or the relative magnitude between the flexural and shear capacity within the inclined section, which affects the failure modes of components. Meanwhile, the adding would reduce the deformation capacity of the components as well. It is suggested that the inclined reinforcement and the constructional reinforcement should be added properly to ensure a desired ductile failure mode for components.

Analysis for Performance Enhancement of TMA using Apodized Time Sequence (Apodized 시계열을 사용한 TMA의 성능 향상에 대한 분석)

  • Ho, Kwang-Chun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.4
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    • pp.105-109
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    • 2018
  • In this paper, the performance enhancement of a time-modulated array is described. The proposed time-modulated array is based on the topology of a conventional array but uses apodized discrete time switching, instead of phase shifters, to achieve beamforming functions with side-band suppression. Numerical simulations are carried out to examine the performance of this beamforming system based on apodized time sequence of 16 elements linear array. Numerical results reveal that the proposed method provides a more flexible and accurate way of producing desired beampatterns with low or ultralow side-lobe level (SLL) compared with the conventional methods.