• 한국농공학회지
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• 제33권2호
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• pp.51-60
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• 1991

The main objective of this study is to examine the adaptability for the large watershed of the storage tank model which can be applied for the analysis of both long and short terms runoff developed on the basis of hydrologic data for a smaH mountaineous watershed. The results obtained in this study are summarized as follows ; 1. Areal rainfalls of the Dae Chong watershed were calculated by Thiessen method composed of 9 Thiessen networks. 2. Optimal parameters for two types, Model A and Model B of tank models were derived through calibration procedure by standardized Powell method. 3. Monthly simulated flows of Model B are seemed to be closer to the monthly observed than those of Model A during calibration period in the long terms runoff. 4. Relative errors for the simulated flood flows of Model B were apperaed as lower percentage to the observed than those of Model A during calibration period in the short terms runoff. 5. Daily simulated hydrographs of Model B are seemed to be closer to the daily observed than those of Model A during verification period in the long terms runoff. Significance of Model B was highly acknowledged in comparison with Model A in the correlation analysis between annual observed and annual simulated runoff. 6. Reproducibility of simulated flows for Model B is generally seemed to be better than that of Model A during calibration period in the short terms runoff. 7. It can be concluded that reproducibility of Model B is superior to that of Model A in the long and short terms runoff even a large watershed like the result of the small one. 8. It was verified that adaptability for the large watershed of Model B is superior to that of Model A between the two models which were developed by a small watershed characteristics for both long and short terms runoff. 9. Further study for getting a suitable tank model is desirable to be established by the decision, calibration method of initial parameters of tank model and by additional application of another watershed with different watersheds and meterological characteristics.

• 한국수자원학회논문집
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• 제42권3호
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• pp.201-212
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• 2009

탱크모형과 PRMS(Precipitation Runoff Modeling-modular System) 모형으로 섬진강댐 유역의 유출량을 1981년부터 2001년까지 모의 발생하였다. 적용된 각각의 단일모형인 Tank 모형과 PRMS 모형에 의하여 모의된 유출량은 서로 상이한 모의 양상을 나타낸다. 본 연구에서는 Tank 모형과 PRMS 모형과 같은 단일모형에 의하여 모의되는 유출량의 편차를 최소화하고 관측유출량에 보다 잘 부합되는 유출모의결과를 생산하기 위하여 유전자 알고리즘 혼합유출모형을 제안하였다. 제안된 혼합유출모형은 Tank 모형과 PRMS 모형의 각각 결과를 혼합하는 모형이며, 유전자 알고리즘을 적용하여 모의 유출량과 관측 유출량을 최소화하는 Tank 모형과 PRMS 모형에 의한 각각의 유출량의 비율을 결정하는 최적배합비를 산정하였다. 제안된 혼합 모형을 섬진강댐 유역에 적용한 결과, Tank 모형 또는 PRMS 모형과 같은 단일모형으로 유출량을 모의하는 경우보다 두 개의 모형을 적절한 배합비를 도입한 혼합 모형으로 모의된 유출량은 관측유출량과의 각종오차를 작게 하는 것을 보여 주었다.

• 한국병원경영학회지
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• 제11권3호
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• pp.19-41
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• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• 대한치과보철학회지
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• 제29권1호
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• pp.233-248
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• 1991

The purpose of this study was to qunatatively analyze the stress patterns induced in the abutment, superstructure, supporting bone and to determine the deflection of abutment and superstructure by appling occlusal force to natural teeth supported fixed prostheses and implant-supported fixed prostheses. The analysis has been conducted by using the two dimensional finite element method. The implant and natural tooth-supported bridge has a first molar pontic supported by mandibular second bicuspid and implant posterior retainer, which were rigidly(Model A) or flexible(Model B). The natural teeth-supported bridge has a first molar pontic supported by mandibular second bicuspid and second molar, which were rigidly splinted together(Model C). 63.5kg(Load P1) of localized load on central fossa of first molar pontic and 24kg(Load P2) of distributed load on each occlusal surface were applied respectively. 1. The coronal portion of premolar pontic and posterior abutment in fixed partial denture deflected inferiorly in order of Model B, Model C and Model A under Load P1 and Load P2. 2. Mesial displacement of the coronal portion of premolar showed in Model A, Model B and Model C under Load P1, but mesial displacement of that in Model B and distal displacement of that in Model A and Model C showed under Load P2. 3. Mesial displacement of the coronal portion of the pontic and distal displacement of the coronal portion of posterior abutment showed in Model A, Model B and Model C under Load P1 and Load P2. Displacement in the case of Model B was greater than that of Model A and Model C. 4. In the case Model A under Load P1 and Load P2, high stress apically was concentrated in the mesiocervical portion of the posterior abutment than in the disto-cervical portion of the premolar. 5. In the case of Model B under Load P1 and Load P2 high stress was concentrated in the case of the premolar than in that of posterior abutment and high stress especially was concentrated in the connected portion of pontic and posterior abutment. 6. In the case of Model C under Load P1 and Load P2, high stress was concentrated in the distal area of the cornal portion of premolar and the mesial area of the coronal portion of posterior abutment, and stress pattern was anteroposterially symmetric around the pontic. 7. Load P1 and Load P2 compared, stress magnitude was different but stress pattern was similar in Model A, Model B and Model C. 8. Under Load P1 and P2, stress magnitude in the mesial distal portion and the portion of root apex of the posterior abutment was in order of Model B, Model A and Model C.

• 한국농공학회논문집
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• 제56권4호
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• pp.9-19
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• 2014

The objective of this study was to evaluate of the Tank model in simulating runoff discharge from rural watershed in comparison to the SWAT (Soil and Water Assessment Tool) model. The model parameters of SWAT was calibrated by the shuffled complex evolution-university Arizona (SCE-UA) method while Tank model was calibrated by genetic algorithm (GA) and validated. Four dam watersheds were selected as the study areas. Hydrological data of the Water Management Information System (WAMIS) and geological data were used as an input data for the model simulation. Runoff data were used for the model calibration and validation. The determination coefficient ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency index (NSE) were used to evaluate the model performances. The result indicated that both SWAT model and Tank model simulated runoff reasonably during calibration and validation period. For annual runoff, the Tank model tended to overestimate, especially for small runoff (< 0.2 mm) whereas SWAT model underestimate runoff as compared to observed data. The statistics indicated that the Tank model simulated runoff more accurately than the SWAT model. Therefore the Tank model could be a good tool for runoff simulation considering its ease of use.

• 생물환경조절학회지
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• 제2권2호
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• pp.126-135
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• 1993

Recently, the characteristic of plant production systems in Korea has been changed with the strong trends of integration and large scale, using environmental control techniques. To satisfy this change successfully, first of all, the environmental prediction inside the system must be preceded. While many environmental prediction models for plant production system were developed by many persons, each model cannot be applied to the every situation without the perfect understanding of source codes and the technical modification. The purpose of this study is building the environmental prediction model to predict and evaluate the environment inside the system numerically, and also developing the multipurpose program available for practical design. The model consisted of the basic system model, the cultivation related model and the environmental control related model. The contents of each model are as follows : the basic system model is dealing with thermal and light environments, soil environment and ventilation : the cultivation related model with soil and hydroponic cultures ; and the environmental control related model with thermal curtain and heat exchanging system. The environmental prediction model was developed using a common simulation program, PCSMP, so that it could be easily understood and modified by anyone. Finally, the model was executed and verified through comparison between simulated and measured results for soil culture, and both results showed good agreements.

• Structural Engineering and Mechanics
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• 제43권3호
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.298-299
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• 2018

본 연구에서는 의사결정자의 사전정보가 필요하지 않은 DEA 모형들을 대상으로 변별력 평가를 실시하였다. 변별력 평가를 위한 DEA모형으로 Entropy 모형, Bootstrap 모형, Benevolent Cross Efficiency 모형, Aggressive Cross Efficiency 모형, Game Cross Efficiency 모형을 선정하였다. 변별력 평가척도인 변동계수(coefficient of variation)와 중요도(degree of importance) 평가기준을 이용하여 5개 DEA 모형의 변별력을 평가하였다. 평가결과에 따르면 변별력 순위는 2개 평가 지표 모두에서 Entropy 모형, Aggressive CE 모형, Benevolent CE 모형, Game CE 모형, Bootstrap 모형 순으로 평가되었다.

• 대한토목학회논문집
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• 제13권4호
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• pp.131-140
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• 1993

기존의 Mualem의 Model III-1에서 공기가 공극으로 진입할 때 이에 대한 공극들의 방해효과를 설명하는 가중치(加重値) $P_a({\theta})$가 무차원 공극반경과 선형적 관계를 가진다는 가정을 바탕으로 하여 모형의 검정을 위하여 한 개의 주곡선이 필요한 새로운 모형을 개발하였다. 개발된 모형은 모형의 검정을 위하여 기존에 제시된 바 있는 한 개의 주곡선이 필요한 모형들보다 실측치를 잘 모의하며, 한쌍의 주곡선이 필요한 영역모형중에서 이력현상을 모형화하는 목적에 가장 부합한 Model III-1과의 비교에서 개발된 모형은 거의 같은 정확성을 가지면서 실측자료를 재현하고 있음을 알 수 있었다. 또한 개발된 모형은 비포화 흐름을 해석할 때 효율적으로 적용될 수 있음을 알 수 있었다.

• 대한기계학회논문집A
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• 제24권10호
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.