• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.147-158
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• 2004

A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.11
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• pp.1231-1236
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• 2007

In this paper, acceleration techniques for a three dimensional ray tracing method are presented. Ray tracing methods are widely adopted to obtain radio propagation channel models, however calculation times increase with the number of scatters such as buildings, hills and mountains. Various techniques are proposed in combination of ray tube concept.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2E
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• pp.68-73
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• 2004

In the East Sea of Korea, the ocean environments are known to have strong variations in space and time. Their effects are very important factors in sound propagation and sonar performance. We consider the environmental factors such as eddies and thermal fronts affecting underwater sound propagation and target detection performance by sonars. Unfortunately, however, the detailed structure of eddies is usually difficult to understand by using the sea surface temperatures from infrared images alone or a few profiles from the CTD (conductivity, temperature and depth) castings. The temperature fields of eddy and thermal front are simulated with typical patterns of those obtained from several observations. This paper delivers the overviews of environments and acoustic models with their simulation results on sonar performance.

• Journal of KSNVE
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• v.7 no.5
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• pp.781-787
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• 1997

A new method is presented to determine two fundamental acoustic quantities of sound-absorbing materials such as characteristic impedance and propagation constant. In this study, the surface acoustic impedances of sound-absorbing materials are measured using the impedance tube and the anechoic chamber to determine the above acoustic quantities. The measured results are given for two typical sound-absorbing materials(glass wool and urethane foam) int the frequency range between 150 and 1, 600 Hz. The results are verified by other two known methods, which are Smith & Parrott method and Utsuno et al. method. The absorption coefficients calculated from the empirical models(Miki model for glass wool and Jung model for urethane foam) and two quantities by present method are in good agreement with the measured values.

• ETRI Journal
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• v.28 no.2
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• pp.247-249
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• 2006

In the development of a new wireless communications system, a versatile and accurate radio channel for indoor communications is needed. In particular, the investigation of radio transmission into buildings is very important. In this letter, we present an improved three-dimensional electromagnetic wave propagation prediction model for indoor wireless communications that takes into consideration building penetration loss. A ray tracing technique based on an image method is also employed in this study. Three-dimensional models can predict any complex indoor environment composed of arbitrarily shaped walls. A speed-up algorithm, which is a modified deterministic ray tube method, is also introduced for efficient prediction and computation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.876-876
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• 2001

Axisymmetric finite element model is developed to determine sound propagation characteristics in a circular duct lined with a poroelastic foam. The foam and air models are derived based on the Biot's theory and the Helmholtz equation respectively and finally result in a quadratic eigenvalue problem in the wave number. Some cross sectional mode shapes are shown and sound attenuations and phase speeds of some acoustic modes are given. Those of fundamental modes are compared with those by forced response solutions and those from measurement results. The influence of lining thickness is also described on sound propagation characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.69-80
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• 1993

It is important to prevent roll failure in hot rolling process for reducing maintenance coat and production loss. Roll material and rolling conditions such as the roll force and torque have been intensively investigated to overcome the roll failures. In this study, a computer roll life prediction system under working condition is developed and evaluated on IBM-PC level. The system is composed and fatigue estimation models which are stress analysis, crack propagation, wear and fatigue estimation. Roll damage can be predicted by calculating the stress anplification, crack depth propagation and fatigue level in the roll using this computer model. The developed system is applied to a work roll in actual hot rolling process for reliability evaluation. Roll failures can be diagnosed and the propriety of current working condition can be determined through roll life prediction simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1249-1253
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• 2005

This paper presents a method to model the path loss characteristics in microwave urban line-of-sight (LOS) propagation. We propose new upper- and lower-bound models for the LOS path loss using fuzzy linear regression (FLR). The spread of upper- and lower-bound of FLR depends on max and min value of a sample path loss data while the conventional upper- and lower-bound models, the spread of the bound intervals are fixed and do not depend on the sample path loss data. Comparison of our models to conventional upper- and lower-bound models indicate that improvements in accuracy over the conventional models are achieved.