• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.153-161
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• 2004

A vehicle fuel economy is one of the most important issues in view of environmental regulation and customer's needs. In order to improve the vehicle fuel economy, great efforts has been carried out on the components bases. However, systematic analysis of vehicle fuel consumption is necessary for the further improvement of vehicle fuel economy. In this paper, a methodology for the breakdown of vehicle fuel consumption was studied and proposed for systematic analysis of the vehicle fuel economy. The energy equation for the vehicle power train was set up for the analysis of the vehicle fuel economy and simplified to be calculated or estimated using the measured data in a vehicle. The amount of fuel that was used in vehicle components under arbitrary driving conditions was quantified.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.306-314
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• 2000

In this paper we present a new approach to estimate link travel speed based on the hybrid neuro-fuzzy network. It combines the fuzzy ART algorithm for structure learning and the backpropagation algorithm for parameter adaptation. At first, the fuzzy ART algorithm partitions the input/output space using the training data set in order to construct initial neuro-fuzzy inference network. After the initial network topology is completed, a backpropagation learning scheme is applied to optimize parameters of fuzzy membership functions. An initial neuro-fuzzy network can be applicable to any other link where the probe car data are available. This can be realized by the network adaptation and add/modify module. In the network adaptation module, a CBR(Case-Based Reasoning) approach is used. Various experiments show that proposed methodology has better performance for estimating link travel speed comparing to the existing method.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.9-22
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• 2008

As an extension of a previous work by the authors (Song and Esogbue, 2006), a new algorithm for automated modeling of nonstationary seasonal time series is presented in this paper. Issues relative to the methodology for building automatically seasonal time series models and periodic time series models are addressed. This is achieved by inspecting the trend, estimating the seasonality, determining the orders of the model, and estimating the parameters. As in our previous work, the major instruments used in the model identification process are correlograms of the modeling errors while the least square method is used for parameter estimation. We provide numerical illustrations of the performance of the new algorithms with respect to building both seasonal time series and periodic time series models. Additionally, we consider forecasting and exercise the models on some sample time series problems found in the literature as well as real life problems drawn from the retail industry. In each instance, the models are built automatically avoiding the necessity of any human intervention.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1943-1945
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• 2001

In this paper, we present an adaptive output feedback control scheme for a class of uncertain nonlinear output-feedback form with time-varying parameters to which adaptive observer backstepping technique may not be applicable directly. In observer design, with the introduction of design function, we can deal with time-varying parameters in a very effective way. By the presented scheme, estimation error can be tuned to a desired small region around the origin via the design constants. Consequently, the observer with the presented design functions and the backstepping methodology achieve a robust regulation of the output tracking error while maintaining boundedness of all the signals and states.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.44-50
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• 2004

The conventional sliding mode control(SMC) technique requires a prior knowledge of the upperbounds of external disturbance to guarantee a robust control performance. This, however, may not be easy to identity in practice. This paper presents a new methodology, sliding mode control with disturbance estimator(SMCDE), which offers a robust control performance without a prior knowledge of the upperbounds. The proposed technique is featured by an integrated average value of the imposed disturbance over a certain period. The proposed technique is applied to the position control of AC servo motor, and experimental results are compared between the conventional and proposed schemes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.66-70
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• 2005

Noise prediction are required as part of an environmental impact assessment. Prediction method that is used to domestic environmental impact assessment of construction site and industrial site is not applied work operation rate, work position, moving noise source, inner traffic flow, work type and height of noise source etc. The BS5228 methodology is used mainly for assessment of proposed open industrial sites(mineral extraction, landfill etc.), and larger long-term construction sites(typically for major infrastructure projects). also, estimation which consider various effect factor is possible.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.7
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• pp.205-212
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• 2020

Defects are an important factor in the quality of software developments. In order to manage defects, we propose additional information of search and classification. Additional information suggests a systematic classification scheme and method of operation. In this study, we propose additional information at the requirements analysis stage for defect management.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.380-380
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• 2018

전 세계적으로 기후변화로 인한 풍수해 피해가 증가하고 있으며 그로 인한 여러 가지 대책이 추진되고 있는 실정이다. 최근 우리나라는 10년간 매년 풍수해로 인해 발생하는 피해액은 약 3천 5백억 원에 해당될 만큼 많은 피해가 발생되고 있기 때문에(행정안전부, 2016), 정확한 홍수취약성을 산정한 후 효율적인 치수대책을 마련할 필요가 있다. 수자원장기종합계획(2001)에서 제시한 홍수피해잠재능(Potential Flood Damage, PFD)은 위험성과 잠재성으로 구성되어 있으며, 대상 지역의 홍수에 대한 취약정도를 나타내는 지수이다. 하지만, 기존의 홍수피해잠재능 산정 방법은 일부 지역에서 발생한 홍수 피해를 평균적인 측면에서 산정하였기 때문에 그 타당성에 문제가 제기되고 있다. 이를 위해, 본 연구에서는 한강의 일부 유역을 대상으로 수자원 장기종합계획에서 제시했던 방법론과 실제 홍수위험지역을 반영한 홍수피해잠재능을 산정한 후 비교 및 고찰하였다.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.341-344
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• 1997

A vitrification process is under development in KEPRI for the treatment of low-and medium-level radioactive waste. Although the project is for developing and building Vitrification Pilot Plant in Korea, one of KEPRI's concerns is the quality control of the vitrified glass. This paper discusses a methodology for the estimation of glass composition by on-line measurement of molten glass properties, which could be applied to the plant for real-time quality control of the glass product. By remotely measuring viscosity and density of the molten glass, the glass characteristics such as composition can be estimated and eventually controlled. For this purpose, using the database of glass composition vs. physical properties in isothermal three-component system of SiO$_2$-Na$_2$O-B$_2$O$_3$, a software TERNARY has been developed which determines the glass composition by using two known physical properties(e.g. density and viscosity).