• 제목/요약/키워드: Least Squares Algorithm

검색결과 564건 처리시간 0.028초

MODELING AND OPTIMIZATION OF THE AIR- AND GAS-SUPPLYING NETWORK OF A CHEMICAL PLANT

  • Han, In-Su;Han, Chong-Hun;Chung, Chang-Bock
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.377-382
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    • 2004
  • This paper presents a novel optimization method for the air- and gas-supplying network comprised of several air compression systems and air and gas streams in an industrial chemical plant. The optimization is based on the hybrid model developed by Han and $Han^1$ for predicting the power consumption of a compression system. A constrained optimization problem was formulated to minimize the total electric power consumption of all the compression systems in the air- and gas-supplying network under various operating constraints and was solved using a successive quadratic optimization algorithm. The optimization approach was applied to an industrial terephthalic acid manufacturing plant to achieve about 10% reduction in the total electric power consumption under varying ambient conditions.

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Hourly Average Wind Speed Simulation and Forecast Based on ARMA Model in Jeju Island, Korea

  • Do, Duy-Phuong N.;Lee, Yeonchan;Choi, Jaeseok
    • Journal of Electrical Engineering and Technology
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    • 제11권6호
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    • pp.1548-1555
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    • 2016
  • This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive - moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island.

상태 관측기를 이용한 자기-동조 적응 제어 (Self-Tuning Adaptive Control Using State Observer)

  • 김윤호;윤병도;오기홍
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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    • pp.223-226
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    • 1991
  • In this paper, the problem of designing on adaptive controller for dc drives using state observers, which is operated under varying load conditions, is addressed. A robust self-tuning controller that can track a constant reference and reject constant load disturbances is also studied. This scheme is very attractive since the estimates of system parameters are available in real time. Parameter estimation is based on the recursive least squares method and the control algorithm of the pole placement technique. Also, state observer systems are applied. State observer systems are required to estimate the states quickly and exactly without being affected by the disturbances.

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시계열 해석을 이용한 팔운동 근전신호의 기능분리 (Functional Separation of Myoelectric Signal of Human Arm Movements Using Time Series Analysis)

  • 홍성우;남문현
    • 대한전기학회논문지
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    • 제41권9호
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    • pp.1051-1059
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    • 1992
  • In this paper, two general methods using time-series analysis in the functional separation of the myoelectric signal of human arm movements are developed. Autocorrelation, covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation-out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squared error. With the error signals of autoregressive(AR) model, the result showed that the highest success rate was obtained in the case of 4th order, and success rate was decreased with increase of order. Autocorrelation was the method of choice for better success rate. This technique might be applied to biomedical and rehabilitation engineering.

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Estimating 3-D surface geometrical features on the basis of surface curvature consistency

  • Zha, H.B.;Muramatsu, S.;Nagata, T.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.54-59
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    • 1993
  • This paper presents a method of estimating 3-D surface geometrical features that are necessary for 3-D object recognition and image interpretation. The features, such as surface needle maps and curvatures, are computed from range or intensity images. In general, the range and intensity images are prone to noises, and hence the features computed by differentiation calculi on such a noisy image are hardly applicable to industrial recognition tasks. In our approach, we try to obtain a more accurate estimate of the features by using a least-squares minimization procedure subject to local curvature consistency constraints. The algorithm is robust with respect to noises and is completely independent of the viewpoint at which the image is taken. The performance of the ajgoritlim is evaluated using both synthetic data and real intensity images.

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A Study on Modeling of Search Space with GA Sampling

  • Banno, Yoshifumi;Ohsaki, Miho;Yoshikawa, Tomohiro;Shinogi, Tsuyoshi;Tsuruoka, Shinji
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.86-89
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    • 2003
  • To model a numerical problem space under the limitation of available data, we need to extract sparse but key points from the space and to efficiently approximate the space with them. This study proposes a sampling method based on the search process of genetic algorithm and a space modeling method based on least-squares approximation using the summation of Gaussian functions. We conducted simulations to evaluate them for several kinds of problem spaces: DeJong's, Schaffer's, and our original one. We then compared the performance between our sampling method and sampling at regular intervals and that between our modeling method and modeling using a polynomial. The results showed that the error between a problem space and its model was the smallest for the combination of our sampling and modeling methods for many problem spaces when the number of samples was considerably small.

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RLS기반 Natural Actor-Critic 알고리즘을 이용한 트레이딩 전략 (Trading Strategy Using RLS-Based Natural Actor-Critic algorithm)

  • 강대성;김종호;박주영;박경욱
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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    • pp.238-241
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    • 2005
  • 최근 컴퓨터를 이용하여 효과적인 트레이드를 하려는 투자자들이 늘고 있다. 본 논문에서는 많은 인공지능 방법론 중에서 강화학습(reinforcement learning)을 이용하여 효과적으로 트레이딩하는 방법에 대해서 다루려한다. 특히 강화학습 중에서 natural policy gradient를 이용하여 actor의 파라미터를 업데이트하고, value function을 효과적으로 추정하기 위해 RLS(recursive least-squares) 기법으로 critic 부분을 업데이트하는 RLS 기반 natural actor-critic 알고리즘을 이용하여 트레이딩을 수행하는 전략에 대한 가능성을 살펴 보기로 한다.

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유연빔의 피드포워드 능동 충격응답 제어 (Feedforward Active Shock Response Control of a Flexible Beam)

  • 표상호;이영섭;신기홍
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2005년도 춘계학술대회논문집
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    • pp.213-216
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    • 2005
  • Active control method is applied to a flexible beam excited by a shock impulse by focusing on reducing the residual vibrations after the shock input. It is assumed that the shock input can be measured and is always occurred on the same point of the beam. If the system is well identified and the corresponding inverse system is designed reliably, it has shown that a very simple feed-forward active control method may be applied to suppress the residual vibrations without using an error sensor and adaptive algorithm. Both numerical simulation and experimental result show a promising possibility of applying to a practical problem.

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수축을 이용한 파이프 곡면의 복원 (Pipe Surface Reconstruction Using Shrinking)

  • 이인권
    • 한국컴퓨터그래픽스학회논문지
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    • 제5권2호
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    • pp.1-7
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    • 1999
  • 구조화되어있지 않은 점 집합으로부터 파이프 곡면을 복원해 내는 알고리즘을 기술한다. 파이프 곡면은 척추 곡선과 스위핑 구의 반지름으로 정의된다. 수축과 동적 최소자승법에 의해 점 집합은 얇은 곡선 형태로 변환된다. 이 얇은 곡선 형태의 점 집합은 쉽게 척추곡선으로 근사될 수 있다. 얇은 점 집합과 원래 주어진 점 집합의 대응하는 두 점간의 거리로 파이프 곡면을 정의하는 스위핑 구의 반지름을 구할 수 있다.

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Dynamic Human Activity Recognition Based on Improved FNN Model

  • Xu, Wenkai;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제15권4호
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    • pp.417-424
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    • 2012
  • In this paper, we propose an automatic system that recognizes dynamic human gestures activity, including Arabic numbers from 0 to 9. We assume the gesture trajectory is almost in a plane that called principal gesture plane, then the Least Squares Method is used to estimate the plane and project the 3-D trajectory model onto the principal. An improved FNN model combined with HMM is proposed for dynamic gesture recognition, which combines ability of HMM model for temporal data modeling with that of fuzzy neural network. The proposed algorithm shows that satisfactory performance and high recognition rate.