• 제목/요약/키워드: Time-lag model

검색결과 345건 처리시간 0.028초

시간지체 순환신경망모형을 이용한 수문학적 모형화기법 (Hydrologic Modeling Approach using Time-Lag Recurrent Neural Networks Model)

  • 김성원
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2010년도 학술발표회
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    • pp.1439-1442
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    • 2010
  • Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

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시간지연 효과를 고려한 기간 통합 DEA 모형의 개발 (Development of A Multi-Period Integration DEA Model Considering Time Lag Effect)

  • 장연상;정병호
    • 한국경영과학회지
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    • 제37권4호
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    • pp.37-50
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    • 2012
  • The existing DEA models have been devoted to evaluate relative efficiency of DMUs based on multiple input and output factors of a same period. However, a certain kind of lead time can be required to produce outputs using inputs in an organization. R&D evaluation is a typical area with this kinds of time lag. Thus, the purpose of this paper is to develop a new DEA model to deal with time lag effect in performance evaluation. The proposed model is to find relative efficiency of each DMU for each period considering the time lag effect. A case example using a real data set is also given to show the usage or implication of the suggested model. The results are compared with the ones of the CCR model and the multi-periods input model.

시간지연 모델을 이용한 충돌형 분사기의 연소응답 인자 도출 및 정량화에 관한 수치해석적 연구 (A Numerical Study on Quantification of Combustion-Response Parameters of Impinging-Jet Injectors using Time-Lag Model)

  • 손진우;김철진;손채훈
    • 한국연소학회:학술대회논문집
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    • 한국연소학회 2012년도 제45회 KOSCO SYMPOSIUM 초록집
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    • pp.5-7
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    • 2012
  • This study presents relations between the time lag and interaction index of the impinging-jet injectors using time lag model in a model chamber. To analyze the response of the flame, 5% amplitude of oxidizer velocity is artificially perturbed at a resonance frequency. At the mixing point of fuel and oxidizer, which determines the characteristic length, the relationship between velocity perturbation and heat release rate is quantified by combustion parameters of interaction index and time lag. As the improved method to apply the time-lag, the method using the average velocity obtained from numerical results is suggested.

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일관된 지연 효과를 고려한 다기간 DEA 모형 (A Multi-Period Input DEA Model with Consistent Time Lag Effects)

  • 정병호;장연상;이태한
    • 산업경영시스템학회지
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    • 제42권3호
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    • pp.8-14
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    • 2019
  • Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.

기업 R&D 투자의 시차효과 분석 (Analysis on Time Lag Effect of Firm's R&D Investment)

  • 이헌준;백철우;이정동
    • 기술혁신연구
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    • 제22권1호
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    • pp.1-22
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    • 2014
  • R&D 투자는 투입 시점과 산출 시점 사이에 시차(time lag)가 존재한다. 따라서 기업의 R&D 투자와 성과와의 관계를 분석할 때 R&D 투입의 시차효과를 정확히 반영하지 않을 경우 분석에 심각한 오류가 발생할 수 있기 때문에 본 연구는 기업 R&D 투자의 시차 효과의 추정을 목적으로 한다. 시차분포모형의 하나인 Almon 모형을 사용하여 기업의 R&D 투자의 투입 시점과 산출 시점 사이의 시차를 측정하였다. 이를 위해 2002년부터 2009년까지의 기업 패널 데이터를 구축하였다. R&D 투자는 기업의 R&D 투자 금액으로, R&D 성과는 특허 출원 건수로 정의하여 분석을 실시하였고 '투자-산출' 프로세스에 소요되는 시차의 길이를 추정하였다. 분석 결과 전체 기술 영역에서 R&D 투자와 특허 출원 사이의 시차는 1~2년으로 분석되었다. 화학, 금속 및 금속 가공, 전기 및 전자, 정밀 과학, 기계 제조의 다섯 개 산업군에 대해 각각 시차의 길이를 추정하였으며 산업군별로 추정된 시차의 길이에 차이가 존재하였다.

충돌형 분사기의 연소응답 인자 정량화에 관한 수치해석적 연구 (A Numerical Study on Combustion-Response Parameters of Impinging-Jet Injectors for Stability Rating)

  • 손진우;김철진;손채훈
    • 한국추진공학회지
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    • 제17권2호
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    • pp.1-8
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    • 2013
  • 모형 연소실에서 충돌형 분사기의 연소 안정성 평가를 위해 시간지연(time lag)과 간섭인자(interaction index)의 관계를 연구하였다. 산화제 분사 속도의 5%에 해당하는 섭동을 공진주파수로 인위적으로 가진하여 이에 대한 화염의 응답특성을 분석하였다. 연료와 산화제의 혼합지점인 충돌점들, 즉, 특성길이 위치에서 속도섭동과 열방출율 섭동간의 관계를 시간지연 모델을 이용하여 나타내었다. 시간지연을 정량화하는 개선된 방법으로서, 수치해석을 통해 얻은 결과로부터 분사기 출구면으로부터 충돌점까지 평균속도를 이용하는 방법을 제안하였다. 축방향의 평균속도가 증가할수록 시간지연이 짧아지는 경향성을 확인할 수 있었다.

국가연구개발사업의 학술적 성과의 시차효과에 관한 실증적 연구 (An Empirical Study on the Time Lag Effect of the Academic Performance of a National R&D Program)

  • 정병호;천강민;양재경
    • 산업경영시스템학회지
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    • 제35권1호
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    • pp.87-92
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    • 2012
  • This study examines the relationship between R&D investment and subsequent outputs of the research activity. Usually, there is some time difference between the production of research outputs, such as academic papers and application or registration of patents, and the investment of R&D expenditure. The time lag for producing this kind of research outputs should be considered to evaluate the performance of research activity exactly. The purpose of this study is to identify time lag effect between the times of input and output of a R&D activity and to derive the degree of time lag using the data set of a long term R&D program supported by Korean government. A modified Almon model is suggested to identify the time lag effect between input and output of research activities performed by this program. Time-series cross-section data from 16 research centers between 2001 and 2009 are used to find time lag effect.

A STUDY ON THE PARAMETER ESTIMATION OF SNYDER-TYPE SYNTHETIC UNIT-HYDROGRAPH DEVELOPMENT IN KUM RIVER BASIN

  • Jeong, Sang-man;Park, Seok-Chae;Lee, Joo-Heon
    • Water Engineering Research
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    • 제2권4호
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    • pp.219-229
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    • 2001
  • Synthetic unit hydrograph equations for rainfall run-off characteristics analysis and estimation of design flood have long and quite frequently been presented, the Snyder and SCS synthetic unit hydrograph. The major inputs to the Snyder and SCS synthetic unit hydrograph are lag time and peak coefficient. In this study, the methods for estimating lag time and peak coefficient for small watersheds proposed by Zhao and McEnroe(1999) were applied to the Kum river basin in Korea. We investigated lag times of relatively small watersheds in the Kum river basin in Korea. For this investigation the recent rainfall and stream flow data for 10 relatively small watersheds with drainage areas ranging from 134 to 902 square kilometers were gathered and used. 250 flood flow events were identified along the way, and the lag time for the flood events was determined by using the rainfall and stream flow data. Lag time is closely related with the basin characteristics of a given drainage area such as channel length, channel slope, and drainage area. A regression analysis was conducted to relate lag time to the watershed characteristics. The resulting regression model is as shown below: ※ see full text (equations) In the model, Tlag is the lag time in hours, Lc is the length of the main river in kilometers and Se is the equivalent channel slope of the main channel. The coefficient of determinations (r$^2$)expressed in the regression equation is 0.846. The peak coefficient is not correlated significantly with any of the watershed characteristics. We recommend a peak coefficient of 0.60 as input to the Snyder unit-hydrograph model for the ungauged Kum river watersheds

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Two-Stage Estimator Design Using Stable Recursive FIR Filter and Smoother

  • Kim, Jong-Ju;Kim, Jae-Hun;Lyou, Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.2532-2537
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    • 2005
  • FIR(Finite Impulse Response) filter is well known to be ideal for the finite time state-space model, but it requires much computation due to its inherent non-recursive structure especially when the measurement interval grows to a large extent. And often a fixed-lag smoother based on the finite time interval is needed to monitor the soundness of the system model and the measurement model, but the computation burden of FIR-type smoother imposes much restriction of its usage for real-time application. Conventional recursive forms of FIR estimator[1]-[4] could not be used for real time applications, since they are numerically unstable in their recursive equations. To cope with this problem, we suggest a stable recursive form FIR estimator(SRFIR) and its usefulness is demonstrated for designing the real-time fixed-lag smoother on the finite time window through an example of detection of rate bias in the anti-aircraft gun fire control system.

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이산 비선형 시스템에 대한 유한 임펄스 응답 고정 시간 지연 평활기 (A Finite Impulse Response Fixed-lag Smoother for Discrete-time Nonlinear Systems)

  • 권보규;한세경;한수희
    • 제어로봇시스템학회논문지
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    • 제21권9호
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    • pp.807-810
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    • 2015
  • In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.