• Title/Summary/Keyword: Data Reference Model

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Estimating Reference Crop Evapotranspiration Using Artificial Neural Network and Temperature-based Climatic Data (인공신경망모형을 이용한 기온기반 기준증발산량 산정)

  • Lee, Sung-Hack;Kim, Maga;Choi, Jin-Yong;Bang, Jehong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.1
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    • pp.95-105
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    • 2019
  • Evapotranpiration (ET) is one of the important factor in Hydrological cycle and irrigation planning. In this study, temperature-based artificial neural network (ANN) model for daily reference crop ET estimation was developed and compared with reference crop evapotranpiration ($ET_0$) from FAO-56 Penman-Monteith method (FAO-56 PM) and parameter regionalized Hargreaves method. The ANN model was trained and tested for 10 weather stations (5 inland stations and 5 costal stations) and two input climate factors, maximum temperature ($T_{max}$), minimum temperature ($T_{min}$), and extraterrestrial radiation (RA) were used for training and validation of temperature-based ANN model. Monthly reference ET by the ANN model also compared with parameter regionalized Hargreaves method for ANN model applicability evaluation. The ANN model evapotranspiration demonstrated more accordance to FAO-56 PM evapotranspiration than the $ET_0$ from parameter regionalized Hargreaves method(R-Hargreaves). The results of this study proposed that daily reference crop ET estimated by the ANN model could be used in the condition of no sufficient climate data.

Bayesian Model Selection in Weibull Populations

  • Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1123-1134
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    • 2007
  • This article addresses the problem of testing whether the shape parameters in k independent Weibull populations are equal. We propose a Bayesian model selection procedure for equality of the shape parameters. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian model selection procedure based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real example are provided.

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Reference Prior and Posterior in the AR(1) Model

  • Lee, Yoon-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.1
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    • pp.71-78
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    • 2005
  • Recently an important issue in Bayesian methodology is determination of noninformative prior distributions, often required when there is no idea of prior information. In this thesis attention is focused on the development of noninformative priors for stationary AR(1) model. The noninformative priors primarily discussed are the Jeffreys prior, and the reference priors. The remarkable points in the result are that the Jeffreys prior coincides with the reference prior for the case that $\rho$ is the parameter of interest.

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A study on Voice Recognition using Model Adaptation HMM for Mobile Environment (모델적응 HMM을 이용한 모바일환경에서의 음성인식에 관한 연구)

  • Ahn, Jong-Young;Kim, Sang-Bum;Kim, Su-Hoon;Hur, Kang-In
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.175-179
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    • 2011
  • In this paper, we propose the MA(Model Adaption) HMM that to use speech enhancement and feature compensation. Normally voice reference data is not consider for real noise data. This method is not to use estimated noise but we use real life environment noise data. And we applied this contaminated data for recognition reference model that suitable for noise environment. MAHMM is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use MAHMM.

Automatic Tuning of Multi-Loop PID Controller (다중루프 PID 제어기의 자동 동조)

  • ;Zeungnam Bien
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.5
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    • pp.478-484
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    • 1990
  • An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.

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A Fundamental Study on the Standardization of Reference Model and Data Model in Digital Twin for Land (디지털 트윈 국토 참조 모델 및 데이터 모델 표준 구축을 위한 기초 연구)

  • Kim, Byeongsun;Yoo, Jaejun;Hong, Sangki
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.1
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    • pp.5-22
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    • 2021
  • Digital Twin for Land(DTL) is one of the national work projects in the Korean New Deal but there aren't still any standards and technical guides which would need to construct the DTL. This study presents the policies to develop reference model and data model based on geo-spatial information standards to ensure interoperability for the DTL. In this paper, we first extract the implications through reviewing definitions of Digital Twin used in various literatures and international standardization trends on Digital Twin. In addition, this study attempts to conceptualize the DTL through various ways such as defining the DTL and characterizing DTL domains. Finally, we propose three policies on the standardization of the DTS: (1) DTS reference model by using RM-ODP, (2) three-steps hierarchical data models, and (3) model registry to manage the data models efficiently. The proposed policies of the study would contribute to establish a way for DTS's standards development over the coming years.

The Study of Data Classification Rethesis on Korea Government DRM (Data Reference Model) - The Establishment of New Data Principal, Classfication and Case Verification - (범정부 데이터 참조모형 데이터 분류체계 재정립에 관한 연구 - 데이터 분류 원칙, 체계수립 및 사례 검증 -)

  • Koo, Ja-Myon;Park, Joo-Seok;Shin, Daul
    • Journal of Information Technology and Architecture
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    • v.9 no.2
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    • pp.187-197
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    • 2012
  • The investment on informatization has caused the increase in complexity of IT resources as well as inefficiency of Information system management and redundant investment. Thus, the idea of EA (Enterprise Architecture) was developed in order to manage the IT resources efficiently but the systematical guideline was insufficiently provided in data area.. Because of this, it is necessary to make full use of DRM (Data Reference Model) so we can enhance the sharing and reuse of data between several institutions in public sector by extracting and managing data behind processes. In this study, we recognize the necessity of improvement on data classification which is highly utilized and present the direction for the data classification rethesis.

Neutral Reference Model for the Sharing and Propagation of Engineering Change Information in a Collaborative Engineering Development (협업 개발 내 설계 변경 정보의 공유 및 전파를 위한 중립 참조 모델)

  • Hwang, Jin-Sang;Mun, Du-Hwan;Han, Soon-Hung
    • Korean Journal of Computational Design and Engineering
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    • v.13 no.4
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    • pp.243-254
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    • 2008
  • As modular production becoming increasingly widespread in globalized manufacturing industries, sub modules or parts of the final product are being provided by many suppliers. Some part suppliers design their own products for themselves. In some cases, part suppliers provide the same type of product to multiple OEM companies. Because all part suppliers and OEM companies typically cannot use the same CAD system, engineering change in the CAD model of one company cannot be directly propagated to related CAD models of other companies. Even if two companies use the same CAD system, it may be difficult to share their CAD model owing to corporate security policy. In this paper, a neutral reference model that consists of a neutral skeleton model and an external reference data model is proposed as a new medium for the sharing and propagation of engineering change information among collaborating companies.

Pan Evaporation and Reference Evapotranspiration Modeling using Neural Networks and Genetic Algorithm (인공신경망과 유전자 알고리즘을 이용한 증발접시 증발량과 증발산량의 모형화)

  • Kim, Seong-Won;Kim, Hyeong-Su;Ji, Hong-Gi
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.115-119
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    • 2006
  • The goal of this research is to develop and apply the generalized regression neural networks model (GRNNM) embedding genetic algorithm (GA) for pan evaporation, which is missed or ungaged and for the alfalfa reference evapotranspiration, which is not measured in South Korea. The GRNNM-GA is evaluated using the training, the testing, and reproduction performance respectively for the estimation of the PE and the alfalfa reference evapotranspiration. Since the observed data of the alfalfa reference evapotranspiration using lysimeter have not been measured for a long time in South Korea, the PM method is used to assume and estimate the observed alfalfa reference evapotranspiration. From this research, we evaluate the impact of the limited climatical variables on the accuracy of the GRNNM-GA. We should, furthermore, construct the credible data of the PE and the alfalfa reference evapotranspiration and suggest the reference data for irrigation and drainage networks system in South Korea.

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PARAMETER IDENTIFICATION FOR NONLINEAR VISCOELASTIC ROD USING MINIMAL DATA

  • Kim, Shi-Nuk
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.461-470
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    • 2007
  • Parameter identification is studied in viscoelastic rods by solving an inverse problem numerically. The material properties of the rod, which appear in the constitutive relations, are recovered by optimizing an objective function constructed from reference strain data. The resulting inverse algorithm consists of an optimization algorithm coupled with a corresponding direct algorithm that computes the strain fields given a set of material properties. Numerical results are presented for two model inverse problems; (i)the effect of noise in the reference strain fields (ii) the effect of minimal reference data in space and/or time data.