• Title/Summary/Keyword: Evaluation parameter

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Development of Parameter Evaluation Model for Calculating Railroad Line Capacity (철도선로용량 계산을 위한 모수 평가모형 개발)

  • 이병권;김학식;이창호;김봉선;김동희
    • Proceedings of the Safety Management and Science Conference
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    • 2003.11a
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    • pp.407-412
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    • 2003
  • Railroad line capacity is influenced by Quantitative and Qualitative factors which is applied by parameter to calculate it. But these parameters have been used experiential value without analyzing its reasonability or appropriate level. In this paper, we introduce the concept of robustness to Quantify parameter and evaluate robustness of it. For this purpose, we develop parameter evaluation simulator and present it. If this simulator is utilized, we can find the parameter having appropriate robustness and it will be applied to calculate more reasonable and systematic railroad line capacity.

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Simulation Input Modeling : Sample Size Determination for Parameter Estimation of Probability Distributions (시뮬레이션 입력 모형화 : 확률분포 모수 추정을 위한 표본크기 결정)

  • Park Sung-Min
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.1
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    • pp.15-24
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    • 2006
  • In simulation input modeling, it is important to identify a probability distribution to represent the input process of interest. In this paper, an appropriate sample size is determined for parameter estimation associated with some typical probability distributions frequently encountered in simulation input modeling. For this purpose, a statistical measure is proposed to evaluate the effect of sample size on the precision as well as the accuracy related to the parameter estimation, square rooted mean square error to parameter ratio. Based on this evaluation measure, this sample size effect can be not only analyzed dimensionlessly against parameter's unit but also scaled regardless of parameter's magnitude. In the Monte Carlo simulation experiments, three continuous and one discrete probability distributions are investigated such as ; 1) exponential ; 2) gamma ; 3) normal ; and 4) poisson. The parameter's magnitudes tested are designed in order to represent distinct skewness respectively. Results show that ; 1) the evaluation measure drastically improves until the sample size approaches around 200 ; 2) up to the sample size about 400, the improvement continues but becomes ineffective ; and 3) plots of the evaluation measure have a similar plateau pattern beyond the sample size of 400. A case study with real datasets presents for verifying the experimental results.

Performance evaluation and simulations of control systems with parameter perturbation (매개변수 섭동에 대한 제어계의 성능 평가 및 시뮬레이션)

  • Yun, Kyong-Han;Lee, Jong-Gun;Hur, Myung-Joon;Kim, Young-Chol
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.330-332
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    • 1992
  • This paper tries to evaluate the control performance of systeme in cases of parameter perturbations. Six cases of the root distribution and location changes of each characteristic roots by the parameter perturbation are considered as evaluation factors. A qualitative evaluation is performed through several simulations. These results will be used as a basic data for the complete analysis of the control performance.

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Quantitative Evaluation Technique for Healing Fractured Bones Using Ultrasound (초음파를 이용한 골절치유과정의 정량적 평가기법)

  • 최흥호
    • Journal of Biomedical Engineering Research
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    • v.16 no.3
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    • pp.359-366
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    • 1995
  • The parameter, B/A, quantifies nonlinearity of the pressure-density relationship of propagation medium. This study investigated quantitative evaluation technique for healing fractured bones using this ultrasonic nonlinear parameter, B/A, obtained by the second harmonic amplitude method. A series of fundamental experiments were performed on cylinder phantoms made of aluminium, which demonstrated potential capability of nonlinear parameter B/A in the diagnosis of healing fractured bones using ultrasound.

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An Extended Model Evaluation Method using Multiple Assessment Indices (MAIs) under Uncertainty in Rainfall-Runoff Modeling (강우-유출 모델링의 불확실성 고려한 다중 평가지수에 의한 확장형 모형평가 방법)

  • Lee, Gi-Ha;Jung, Kwan-Sue;Tachikawa, Yasuto
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.591-595
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    • 2010
  • Conventional methods of model evaluation usually rely only on model performance based on a comparison of simulated variables to corresponding observations. However, this type of model evaluation has been criticized because of its insufficient consideration of the various uncertainty sources involved in modeling processes. This study aims to propose an extended model evaluation method using multiple assesment indices (MAIs) that consider not only the model performance but also the model structure and parameter uncertainties in rainfall-runoff modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250m, 500m, and 1km digital elevation models) were developed and assessed by three MAIs for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. In addition, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. Numerous parameter sets could lead to indistinguishable hydrographs. This result supports that while making a model complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty. The proposed model evaluation process can provide an effective guideline for identifying a reliable hydrologic model.

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Weighted Parameter Analysis of L1 Minimization for Occlusion Problem in Visual Tracking (영상 추적의 Occlusion 문제 해결을 위한 L1 Minimization의 Weighted Parameter 분석)

  • Wibowo, Suryo Adhi;Jang, Eunseok;Lee, Hansoo;Kim, Sungshin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.101-103
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    • 2016
  • Recently, the target object can be represented as sparse coefficient vector in visual tracking. Due to this reason, exploitation of the compressibility in the transform domain by using L1 minimization is needed. Further, L1 minimization is proposed to handle the occlusion problem in visual tracking, since tracking failures mostly are caused by occlusion. Furthermore, there is a weighted parameter in L1 minimization that influences the result of this minimization. In this paper, this parameter is analyzed for occlusion problem in visual tracking. Several coefficients that derived from median value of the target object, mean value of the arget object, the standard deviation of the target object are, 0, 0.1, and 0.01 are used as weighted parameter of L1 minimization. Based on the experimental results, the value which is equal to 0.1 is suggested as weighted parameter of L1 minimization, due to achieved the best result of success rate and precision performance parameter. Both of these performance parameters are based on one pass evaluation (OPE).

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An Extended Model Evaluation Method under Uncertainty in Hydrologic Modeling

  • Lee, Giha;Youn, Sangkuk;Kim, Yeonsu
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.5
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    • pp.13-25
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    • 2015
  • This paper proposes an extended model evaluation method that considers not only the model performance but also the model structure and parameter uncertainties in hydrologic modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250-m, 500-m, and 1-km digital elevation models) were developed and assessed by three evaluative criteria for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. Moreover, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. A number of parameter sets could result in indistinguishable hydrographs. This result indicates that while making hydrologic models complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty.

Line Capacity Analysis and Capacity Parameter Evaluation (선로용량 분석체계와 용량모수평가)

  • Kim Dong-Hee;Hong Soon-Heum;Kim Young-Hoon
    • Proceedings of the KSR Conference
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    • 2004.10a
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    • pp.1559-1565
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    • 2004
  • Railway system is consisted of various resources such as rail-line, signal, and railcar. It is necessary to efficiently utilize these limited and expensive resources as much as possible up to given line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present an improved systematic line capacity model. The proposed model has three main components ; TPS(tain performance simulator), PES (parameter evaluation simulator), LCS(line capacity simulator). The concept of each sub-component is described, including the evaluation method of capacity parameters. And capacity parameter evaluation and estimation results using sample line section data are presented.

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A Study on Comparative Estimate with Development of Reliability Estimation Model in Applicable of Field to Existing Model Using Error Occurrence Density Function (오류발생밀도함수를 이용한 현장 적용형 신뢰성 평가모형 개발과 기존 모형과의 비교평가에 관한 연구)

  • Kim, Suk-Hee;Kim, Jong-Hun;Shinn, Seong-Whan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.2
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    • pp.63-71
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    • 2010
  • The existing reliability evaluation models which have already developed by the corporations are so various because of using Maximum Likelihood Method. The existing models are very complicated owing to using system designing methods. Therefore, it is very difficult to utilize the existing models in business fields of many corporations. The purposes of this paper are as follows: The first purpose is to study the simple estimated Parameter to be easily utilized in the business fields of the corporations. The second purpose is to testify the simplification of the developed Parameter of estimated method by comparing the developed reliability evaluation model with the existing reliability evaluation models which are used in the business fields of the corporations.

Fundamental Small-signal Modeling of Li-ion Batteries and a Parameter Evaluation Using Levy's Method

  • Zhang, Xiaoqiang;Zhang, Mao;Zhang, Weiping
    • Journal of Power Electronics
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    • v.17 no.2
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    • pp.501-513
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    • 2017
  • The fundamental small-signal modeling of lithium-ion (Li-ion) batteries and a parameter evaluation approach are investigated in this study to describe the dynamic behaviors of small signals accurately. The main contributions of the study are as follows. 1) The operational principle of the small signals of Li-ion batteries is revealed to prove that the sinusoidal voltage response of a Li-ion battery is a result of a sinusoidal current stimulation of an AC small signals. 2) Three small-signal measurement conditions, namely stability, causality, and linearity, are proved mathematically proven to ensure the validity of the frequency response of the experimental data. 3) Based on the internal structure and electrochemical operational mechanism of the battery, an AC small-signal model is established to depict its dynamic behaviors. 4) A classical least-squares curve fitting for experimental data, referred as Levy's method, are introduced and developed to identify small-signal model parameters. Experimental and simulation results show that the measured frequency response data fit well within reading accuracy of the simulated results; moreover, the small-signal parameters identified by Levy's method are remarkably close to the measured parameters. Although the fundamental and parameter evaluation approaches are discussed for Li-ion batteries, they are expected to be applicable for other batteries.