• 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.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.19-26
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• 2008

In this paper, we propose a dynamic prediction algorithm to predict the bond price using actual data set of treasure note (T-Note). The proposed algorithm is based on term structure model of the interest rates, which takes place in various financial modelling, such as the standard Gaussian Wiener process. To obtain cumulative distribution functions (CDFs) of actual data for the interest rate measurement used, we use the natural cubic spline (NCS) method, which is generally used as numerical methods for interpolation. Then we also use the random number generation scheme (RNGS) to calculate the pricing of bond through the obtained CDF. In empirical computer simulations, we show that the lower values of precision in the proposed prediction algorithm corresponds to sharper estimates. It is very reasonable on prediction.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.748-753
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• 2005

Among processes to manufacture parts from footwear materials like upper leathers, one of the most essential processes is the cutting one optimally arranging lots of parts on raw footwear materials and cutting. A new nesting strategy was proposed for the 2-dimensional part layout by using a two-stage approach, where which can be effectively used for water jet cutting. In the initial layout stage, a SOAL(Self-Organization Assisted Layout) based on the combination of FCM(Fuzzy C-Means) and SOM was adopted. In the layout improvement stage, SA(Simulated Annealing) based approach was adopted for a finer layout. The proposed approach saves much CPU time through a two-stage approach scheme, while other annealing-based algorithm so far reported fur a nesting problem are computationally expensive. The proposed nesting approach uses the stochastic process, and has a much higher possibility to obtain a global solution than the deterministic searching technique. We developed the automatic nesting software of NST(ver.1.1) software for footwear industry by implementing of these proposed algorithms. The NST software was applied by the optimized automatic arrangement algorithm to cut without the loss of leathers. if possible, after detecting damage areas. Also, NST software can consider about several features in not only natural loathers but artificial ones. Lastly, the NST software can reduce a required time to implement generation of NC code. cutting time, and waste of raw materials because the NST software automatically performs parts arrangement, cutting paths generation and finally NC code generation, which are needed much effect and time to generate them manually.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.393-417
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• 2022

Using hourly SMP data from 2016 to 2020, this paper measures the weekly realized volatility and investigates the main force of its determinants. To this end, we extend the Bayesian variable selection by incorporating the regime-switching model which identifies important variables among a large number of predictors by regimes. We find that the increase in coal and nuclear generation, as well as solar power, reinforce the SMP volatility in both high volatility and low volatility regime. In contrast the increase in gas generation and gas price decrease SMP volatility when SMP volatility is high. These results suggest that the expansion of renewable energy according to 2050 Carbon Neutrality or energy transition policies increases SMP volatility but the increase in the gas generation or reduction of coal generation might offset its impact.

• Korean Management Science Review
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• v.22 no.1
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• pp.15-26
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• 2005

The bootstrap is a method of computational inference that simulates the creation of new data by resampling from a single data set. We propose a new job for the bootstrap: generating inputs from one historical trace using Threshold Bootstrap. In this regard, the most important quality of bootstrap samples is that they be functionally indistinguishable from independent samples of the same stochastic process. We describe a quantitative measure of difference between two time series, and demonstrate the sensitivity of this measure for discriminating between two data generating processes. Utilizing this distance measure for the task of generating inputs, we show a way of tuning the bootstrap using a single observed trace. This application of the threshold bootstrap will be a powerful tool for Monte Carlo simulation. Monte Carlo simulation analysis relies on built-in input generators. These generators make unrealistic assumptions about independence and marginal distributions. The alternative source of inputs, historical trace data, though realistic by definition, provides only a single input stream for simulation. One benefit of our method would be expanding the number of inputs achieving reality by driving system models with actual historical input series. Another benefit might be the automatic generation of lifelike scenarios for the field of finance.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.120-131
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• 2004

In this paper, we propose the method of a motion planning generation in which the movement of the 3-link leg subsystem is constrained to a slider-link and a singular posture can be easily avoided. The proposed method is the jumping control moving in vertical direction which mimics a cat's behavior. That is, it is jumping toward wall and kicking it to get a higher-place. Considering the movement from the point of constraint mechanical system, the robotic system which realizes the motion changes its configuration according to the position and it has several phases such as; ⅰ) an one-leg phase, ⅱ) in an air-phase. In other words, the system is under nonholonomic constraint due to the reservation of its momentum. Especially, in an air-phase, we will use a control method using state transformation and linearization in order to control the landing posture. Also, an iterative learning control algorithm is applied in order to improve the robustness of the control. The simulation results for jumping control will illustrate the effectiveness of the proposed control method.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.337-340
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• 2000

In this paper, the effects of the uncertain hourly load demand are stochastically analyzed especially by the consideration of the average over generation of the Unit Commitment(UC) results. In order to minimize the effects of the actual load profile change, a new UC algorithm is proposed. The proposed algorithm calculates the UC results with the lower load level than the one generated by the conventional load forecast. In case of the worse load forecast, the deviation of the conventional UC solution can be overcome with the lower load level and the more hourly reserve requirements. The proposed method is tested with sample systems, which shows that the proposed method can be used as the basic guideline for selecting the potimal load forecast applying to UC problem.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.3
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• pp.39-47
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• 1990

The generation of artificial accelerograms considering the characteristic of earthquakes in the Korean peninsula for a time history analysis of structures is accomplised by the stochastic method. The engineering data such as a representative shape of envelope function and an effective duration are investigated from the instrumental records. The maximum ground acceleration value is based on seismic zoning map which are constructed for the Korean peninsula. The acceleration-time histories are generated for two different types of earthquake motions and two types of soil conditions. In the study, the maximum ground acceleration value of 0.2 g and effective durations of 24 seconds are used. The validity of the artificial accelerograms is obtained by the comparison with the required envelope functions and the design response spectrum.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.2
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• pp.31-40
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• 1995

This study was conducted to get best fitting frequency distribution for the annual run- off and to simulate long series of annual flows by single-season first order Markov Model with comparison of statistical parameters which were derived from observed and synthetic flows at four watersheds in Seom Jin and Yeong San river systems. The results summarized through this study are as follows. 1. Hydrologic persistence of observed flows was acknowledged by the correlogram analysis. 2. A normal distribution of the annual runoff for the applied watersheds was confirmed as the best one among others by Kolmogorov-Smirnov test. 3. Statistical parameters were calculated from synthetic flows simulated by normal dis- tribution. In was confirmed that mean and standard deviation of simulated flows are much closer to those of observed data than except coefficient of skewness. 4. Hydrologic persistence between observed flows and synthetic flows simulated was also confirmed by the correlogram analysis. 5. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.