• 제목/요약/키워드: Problem Decomposition

검색결과 586건 처리시간 0.031초

다회방문을 허용하는 차량경로문제의 발견적 해법 (A Heuristic for the Vehicle Routing Problem Allowing Multiple Visits)

  • 신해웅;강맹규
    • 산업경영시스템학회지
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    • 제14권24호
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    • pp.141-147
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    • 1991
  • This paper presents extended model for the vehicle routing problem, which allows multiple visits to a node by multiple vehicles. Multiple visits enables us split delivery. After formulating this multiple visits model mathematically, a two stage heuristic algorithm is developed by decomposition approach. This model consists of two sub-problem. The one is fixed cost transportation problem and the other is transportation problem.

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Bitcoin Price Forecasting Using Neural Decomposition and Deep Learning

  • 마렌드라;김나랑;이태헌;유승의
    • 한국산업정보학회논문지
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    • 제23권4호
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    • pp.81-92
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    • 2018
  • Bitcoin is a cryptographic digital currency and has been given a significant amount of attention in literature since it was first introduced by Satoshi Nakamoto in 2009. It has become an outstanding digital currency with a current market capitalization of approximately $60 billion. By 2019, it is expected to have over 5 million users. Nowadays, investing in Bitcoin is popular, and along with the advantages and disadvantages of Bitcoin, learning how to forecast is important for investors in their decision-making so that they are able to anticipate problems and earn a profit. However, most investors are reluctant to invest in bitcoin because it often fluctuates and is unpredictable, which may cost a lot of money. In this paper, we focus on solving the Bitcoin forecasting prediction problem based on deep learning structures and neural decomposition. First, we propose a deep learning-based framework for the bitcoin forecasting problem with deep feed forward neural network. Forecasting is a time-dependent data type; thus, to extract the information from the data requires decomposition as the feature extraction technique. Based on the results of the experiment, the use of neural decomposition and deep neural networks allows for accurate predictions of around 89%.

개선된 앙상블 EMD 방법을 이용한 데이터 기반 신호 분해 (Data-Driven Signal Decomposition using Improved Ensemble EMD Method)

  • 이금분
    • 한국정보통신학회논문지
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    • 제19권2호
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    • pp.279-286
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    • 2015
  • EMD는 미리 정의된 어떠한 기저함수도 사용하지 않으며 사용자에 의해 미리 정의된 파라미터값도 필요치 않은 완전히 데이터에 기반한 신호 처리의 특징을 갖는다. 그러나 유사한 스케일을 갖는 신호 모드로 분해하는 것을 방해하는 모드 혼합이 발생하는 단점이 있다. 이를 해결하기 위해 EEMD 알고리즘이 도입되었으며, EEMD는 처리하고자 하는 신호에 가우시안 백색 잡음을 혼합하여 앙상블 수만큼 신호를 만들어 EMD 방법을 적용함으로써 모드 혼합 문제를 해결한다. 그럼에도 EEMD는 잡음이 추가된 신호 분해 시 원 신호와 상이한 모드 수를 만들어 내며, 분해된 신호들을 원 신호로 재구성 시에도 레지듀 잡음이 포함된다. 본 논문은 개선된 EEMD알고리즘으로 EMD의 모드 혼합 문제를 해결하고 원신호를 정확히 재구성하며 EEMD 보다 적은 연산 비용으로 신호 모드 분리를 제안한다. 실험결과는 EEMD 방법과 비교하여 적은 체과정의 반복으로 빠른 모드 분리를 보여 주었으며 EEMD 방법의 20.87%의 비용만으로 완전한 신호 분해가 가능하였고, 신호 복원에 있어서도 EEMD 보다 우수한 성능을 보여주었다.

A generalized adaptive variational mode decomposition method for nonstationary signals with mode overlapped components

  • Liu, Jing-Liang;Qiu, Fu-Lian;Lin, Zhi-Ping;Li, Yu-Zu;Liao, Fei-Yu
    • Smart Structures and Systems
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    • 제30권1호
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    • pp.75-88
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    • 2022
  • Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

시간제약하의 네트워크 신뢰성 계산에 대한 알고리즘 (An Algorithm for Computing the Source-to-Terminal Reliability in the Network with Delay)

  • 홍순식;이창훈
    • 대한산업공학회지
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    • 제12권1호
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    • pp.133-138
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    • 1986
  • In this paper, we are modeling the problem of the reliability evaluation in the network with delay. The triconnected decomposition and factoring algorithm for the network reliability, known as the most efficient algorithm, does not work in this constrained problem. So, we propose some ideas that reduce the above constrained problem to the general network reliability problem. We also present an algorithm for the reliability evaluation in the network with delay based on these ideas.

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특이점 근방에서 역 기구학 해를 구하기 위한 자동 감쇄 분배 방법 (A Damping Distribution Method for Inverse Kinematics Problem Near Singular Configurations)

  • 성영휘
    • 제어로봇시스템학회논문지
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    • 제4권6호
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    • pp.780-785
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    • 1998
  • In this paper, it is shown that the conventional methods for dealing with the singularity problem of a manipulator can be generalized as a local minimization problem with differently weighted objective functions. A new damping method proposed in this article automatically determines the damping amounts for singular values, which are inversely proportional to the magnitude of the singular values. Furthermore, this can be done without explicitly computing the singular values. The proposed method can be applied to all the manipulators with revolute joints.

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상용해석 코드(MSC-Marc)를 활용한 노즐 내열부품의 숯/삭마 해석 기법 (Thermal decomposition and ablation analysis of solid rocket nozzle using MSC.Marc)

  • 김연철
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2009년도 춘계학술대회 논문집
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    • pp.311-314
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    • 2009
  • 고체추진기관의 연소 환경에서 복잡한 형상을 갖는 내열 복합재료의 온도 및 밀도분포를 예측할 수 있는 방법을 개발하였다. 복합재료의 내부 열반응은 Arrhenius 모델을 이용하였으며, 표면 삭마반응은 Zvyagin 이론을 사용하였다. 표면 삭마에 의한 경계조건 및 격자 이동은 Rezoning 기법을 사용하였으며 열분해에 의한 흡열반응 효과는 열분해 가스의 조성비에 기준한 유효 비열 값을 이용하여 계산되었다. 형상이 복잡한 부품으로 이루어진 2차원 축대칭 노즐 조립체에 적용된 방법은 향후 3차원 FEM 열구조 해석에 활용을 목표로 발전될 것이다.

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영역분할법 (domain decomposition)과 TLM법을 이용한 회전기의 비선형 유한 요소 해석 (A Novel Finite Element Technique for analyzing Saturated Rotating Machines Using the Domain Decomposition and TLM Method)

  • 주현우;임창환;이창환;김홍규;정현교
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 B
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    • pp.623-625
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    • 2000
  • For the finite element analysis of highly saturated rotating machines involving rotation of a rotor such as dynamic analysis. cogging torque analysis and etc, so much time is needed because a new system matrix equation should be solved for each iteration and time step. It is proved in this paper that. in linear systems. the computational time can be greatly reduced by using the domain decomposition method (DDM). In nonlinear systems. however. this advantage vanishes because the stiffness matrix changes at each iteration especially when using the Newton-Raphson (NR) method. The transmission line modeling (TLM) method resolves this problem because in TLM method the stiffness matrix does not change throughout the entire analysis. In this paper, a new technique for FEA of rotating machines including rotation of rotor and non-linearity is proposed. This method is applied to a test problem. and compared with the conventional method.

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웨이브릿 변환을 이용한 공간주파수 적응적 영상복원 (Spatial Frequency Adaptive Image Restoration Using Wavelet Transform)

  • 우헌배;기현종;정정훈;신정호;백준기
    • 방송공학회논문지
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    • 제8권2호
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    • pp.204-208
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    • 2003
  • 웨이브릿 변환 기반의 부대역(subband) 분해과정을 새로운 수학적 모델로 표현한다. 제안된 모델은 많은 계층의 분해과정에 거쳐 정규적인 다해상도 해석을 수행할 수 있다. 이러한 접근방식은 단일채널 선형 공간불변 필터링문제를 다채널로 확장할 수 있게 해주는 동시에 선형 공간불변 영상복원문제와 주파수상에서 적응적 제약적 최소제곱(Constrained Least Square:CLS) 필터에 적용될 수 있다. 제안된 필터에서 우리는 부대역의 특징에 따라 적응적으로 다른 변수를 사용할 수 있다. 본 논문에서 제안한 주파수상의 적응적 CLS 필터를 S/W로 구현하였으며, 이 실험을 통해 부대역의 특징을 정화하게 측정할 경우 제안된 주파수상 적응적 CLS 필터는 기존의 단채널 필터에서 벗어나 현저히 화질을 개선할 수 있음을 보여준다.