• Title/Summary/Keyword: Recursive least squares

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Analysis of Hierarchical Competition Structure and Pricing Strategy in the Hotel Industry

  • BAEK, Unji;SIM, Youngseok;LEE, Seul-Ki
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.4
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    • pp.179-187
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    • 2019
  • This study aims to investigate the effects of market commonality and resource similarity on price competition and the recursive consequences in the Korean lodging market. Price comparison among hotels in the same geographic market has been facilitated through the development of information technology, rendering little search cost of consumers. While the literature implies the heterogeneous price attack and response among hotels, a limited number of empirical researches focus on the asymmetric and recursive pattern in the competitive dynamics. This study empirically examines the price interactions in the Korean lodging market based on the theoretical framework of competitive price interactions and countervailing power. Demonstrating superiority to the spatial lag model and the ordinary least squares in the estimation, the results from spatial error model suggest that the hotels with longer operational history pose an asymmetric impact on the price of the newer hotels. The asymmetry is also found in chain hotels over the independent, further implying the possibility of predatory pricing. The findings of this study provide the evidence of a hierarchical structure in the price competition, with different countervailing power by the resources of the hotels. Theoretical and managerial implications are discussed, with suggestions for future study.

Adaptive Nonlinear Constrained Predictive Control of pH Neutralization in Fed-batch Bio-reactor

  • Zhe, Xu;Kim, Hak-Kyeong;Kim, Sang-Bong
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.90-95
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    • 2003
  • In this paper, an Adaptive Nonlinear Constrained Model Predictive Control (ANCMPC) is presented for a pH control in a fed-batch bio-reactor. The pH model is represented with Hammerstein Model. The static nonlinear part of Hammerstein model is described with the static pH model, and the dynamic linear part of the Hammerstein model is described with the CARIMA model. The parameters of the CARIMA model is estimated on-line with the input and output measurements of the system using a recursive least squares type of identi�cation algorithm. The e�ectiveness of the proposed controller is shown through simulations.

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Number Plate Detection System by Using the Night Images

  • Yoshimori, S.;Mitsukura, Y.;Fukumi, M.;Akamatsu, N.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1249-1253
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    • 2003
  • License plate recognition is very important in an automobile society. This is because, since plate detection accuracy has large influence on subsequent number recognition, it is very important. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. In this paper, we propose a new thresholds determination method in the various background by using the real-coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various lighting conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds)are obtained by RGA. The relationship between thresholds decided from RGA and brightness average is aproximate by using the recursive least squares (RLS) algorithm. In the case of plate detection, thresholds are decided from these functions.

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Nonlinear Lattice Algorithms using QRD and Channel Decomposition (QR 분해와 채널 분해법을 이용한 비선형 격자 알고리듬)

  • 안봉만;백흥기
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.10
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    • pp.1326-1337
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    • 1995
  • In this paper, we transformed the bilinear filter into an equivalent linear multichannel filter and derived QR decomposition based recursive least squares algorithms for bilinear lattice filters. We also defined order update relation of the forward and the backward input vectors by using the channel decomposition. The forward and the backward data matrices were defined by using the forward and the backward input vectors and orthogonalized with the QR decomposition. we can obtain the lattice equations of the bilinear filters by using the channel decomposition. we can be derived the lattice equations of the bilinear filters using this decomposition process which are the same as the lattice equations derived by Baik, we can use the coefficient transformation algorithm proposed by Baik. We derived the equation error and the output error algorithm of the QRD based RLS bilinear lattice algorithm. Also, we evaluated the performance of the proposed algorithms through the system identification of the bilinear system.

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Gauss Newton Variable forgetting factor RLS algorithm for Time Varying Parameter Estimation. (Gauss Newton Variable Forgetting Factor Recursive Least Squares 알고리듬을 이용한 시변 신호 추정)

  • Song Seongwook;Lim Jun-Seok;Sung Koeng-Mo
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.173-176
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    • 2000
  • 시변 신호 추적 특성을 향상시키기 위하여, Gauss-Newton Variable Forgetting Factor RLS (GN-VFF-RLS) Algorithm을 제안한다. 최적화된 망각인자를 가정한 기존의 RLS 알고리듬과 비교하여, 제안된 방법은 특히 신호의 변화가 급격히 일어날 경우 주목할만한 추정 성능의 향상을 보여준다. 제안된 알고리듬의 시변 추정 특성을 신호 대 잡음비와 시변 정도에 대하여 모의 실험하고 기존의 추정 알고리듬들과 비교한다.

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

  • Kim, Yoon-Ho;Yoon, Byung-Do;Oh, Gi-Hong
    • Proceedings of the KIEE Conference
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    • 1991.11a
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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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A study on the improvement of DGPS positioning accuracy using a kalman filtering method (칼만 필터를 이용한 DGPS의 위치측정 정확도 향상에 관한 연구)

  • 주세철;오정헌;이창복;김영욱;김기두
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.109-178
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    • 1996
  • For each reference station and user, the proposed DGPS system is implemented by a GPS module and a modem. The reference station makes plans of the receiving schedule from the satellite sets at each period and then provides the correction data for various satellite sets in a period. Users can utilize the correction data continuously and efficiently through the recursive least squares lattice filters. Furthermore, after taking DGPS techniques, we can improve the positioning accuracy using a kalman filter by decreasing anti-common errors between a reference station and a user. Experimental results show the positioning accuracy of better than 5 meters in almost real time.

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Performance Comparison of Crawling Robots Trained by Reinforcement Learning Methods (강화학습에 의해 학습된 기는 로봇의 성능 비교)

  • Park, Ju-Yeong;Jeong, Gyu-Baek;Mun, Yeong-Jun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.33-36
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    • 2007
  • 최근에 인공지능 분야에서는, 국내외적으로 강화학습(reinforcement learning)에 관한 관심이 크게 증폭되고 있다. 강화학습의 최근 경향을 살펴보면, 크게 가치함수를 직접 활용하는 방법(value function-based methods), 제어 전략에 대한 탐색을 활용하는 방법(policy search methods), 그리고 액터-크리틱 방법(actor-critic methods)의 세가지 방향으로 발전하고 있음을 알 수 있다. 본 논문에서는 이중 세 번째 부류인 액터-크리틱 방법 중 NAC(natural actor-critic) 기법의 한 종류인 RLS-NAC(recursive least-squares based natural actor-critic) 알고리즘을 다양한 트레이스 감쇠계수를 사용하여 연속제어입력(real-valued control inputs)으로 제어되는 Kimura의 기는 로봇에 대해 적용해보고, 그 성능을 기존의 SGA(stochastic gradient ascent) 알고리즘을 이용하여 학습한 경우와 비교해보도록 한다.

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

  • Kang Daesung;Kim Jongho;Park Jooyoung;Park Kyung-Wook
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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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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Study of Harmonic Sources Management Method using Control Chart (컨트롤 차트를 이용한 고조파 전압 왜곡 발생원 관리기법 연구)

  • Han, Jong-Hoon;Lee, Key-Byung;Jang, Gil-Soo;Park, Chang-Hyun
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.197-198
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    • 2011
  • A technique to manage harmonic pollution at the point of common coupling (PCC) has been presented using a control chart. The recursive least-squares technique has been used to estimate the parameters of the Thevenin equivalent load model. With the estimated data from the measured voltage and current waveform at the PCC during certain period violating upper control limit, the individual contributions to the distortion of voltage waveform at an interested harmonic frequency have been calculated and shown by simple graph.

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