• Advances in Computational Design
• /
• v.2 no.4
• /
• pp.283-291
• /
• 2017

High frequency full bridge series resonant inverters have become increasingly popular among power supply designers. One of the most important parameter for a High Frequency Full Bridge Series Resonant Inverter is optimal coil design. The optimal coil designing procedure is not a easy task. This paper deals with the New Approach to Optimal Design Procedure for a Real-time High Frequency Full Bridge Series Resonant Inverter in Induction Heating Equipment devices. A new design to experimental modelling of the physical properties and a practical power input simulation process for the non-sinusoidal input waveform is accepted. The design sensitivity analysis with Levenberg-Marquardt technique is used for the optimal design process. The proposed technique is applied to an Induction Heating Equipment devices model and the result is verified by real-time experiment. The main advantages of this design technique is to achieve more accurate temperature control with a huge amount of power saving.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.2
• /
• pp.101-107
• /
• 2010

Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.

• Journal of Industrial Technology
• /
• v.29 no.B
• /
• pp.9-15
• /
• 2009

In the case of traditional binary encoding technique, it takes long time to converge the optimal solutions and brings about complexity of the systems due to encoding and decoding procedures. However, the ROGAs (real-coded genetic algorithms) do not require these procedures, and the k-means clustering algorithm can avoid global searching space. Thus, this paper proposes a new approach by using their advantages. The proposed method constructs the multiple predictors using the optimal differences that can reveal the patterns better and properties concealed in non-stationary time series where the k-means clustering algorithm is used for data classification to each predictor, then selects the best predictor. After selecting the best predictor, the cluster centers of the predictor are tuned finely via RCGKA in secondary tuning procedure. Therefore, performance of the predictor can be more enhanced. Finally, we verifies the prediction performance of the proposed system via simulating typical time series examples.

• Journal of Korea Technical Association of The Pulp and Paper Industry
• /
• v.41 no.3
• /
• pp.49-59
• /
• 2009

The bast fibers of paper mulberry were dyed by using sappan wood, gardenia, and gallnut extracted under various extraction conditions. The surface absorption rates, color, and sunlight fastness of the dyed fibers were compared to those of the dyed cotton and silk. The K/S values of silk showed the highest values, followed by gallnut, gardenia, and sappan wood. The optimum extraction conditions of the dye materials were 20 g/L (input amount of dye materials per liter), $90^{\circ}C$ (extraction temperature), and 30 minutes (extraction time). The values of saturation were observed to increase with the increase of the amount of dye materials, extraction time, and extration temperature. However, no effect were found on the values of hue and lightness. In all samples, the developed colors dyed by sappan wood and gardenia were the series of YR, and Y, respectively. The colors of dyed cotton and bast fibers of paper mulberry by gallnut were the series of Y and the dyed silk showed the series of YR. The values of saturation of the bast fibers of paper mulberry by sappan wood and gardenia showed the highest values of saturation, followed by cotton, and silk. In the case of gallnut, cotton showed the highest values of saturation, followed by the bast fibers of paper mulberry, and silk. The sunlight fastness were not improved in all dyeing conditions.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.6
• /
• pp.71-78
• /
• 1989

The imput-output relations for nonlinear systems can be explicitly represented by the Volterra series and they can be characterized by the Volterra kernels. This study is concerned with modeling an elastomer force-displacement relation due to step inputs by utilizing the truncated Volterra series. Since it is practically impossible to apply step inputs that have infinite slope at zero time, the loads due to constant penetration(displacement) rate followed by constant penetration inputs are measured as an alternative approach and estimated for step inputs and then utilized for the truncated Volterra series models. One second order and one third order truncated Volterra series models have been employed to model the force-displacement relation which is one of the prominent properties to characterize the viscoelastic material. The third order truncated Volterra series model has better results, compared with those of the second order truncated Volterra series model.

• Structural Engineering and Mechanics
• /
• v.88 no.6
• /
• pp.589-598
• /
• 2023

This article addresses the quasi-static analysis of time-dependent honeycomb sandwich plates with various geometrical properties based on the bending analysis of elastic honeycomb sandwich plates employing a time function with three unknown coefficients. The novel point of the developed method is that the responses of viscoelastic honeycomb sandwich plates under static transversal loads are clearly formulated in the space and time domains with very low computational costs. The mechanical properties of the sandwich plates are supposed to be elastic for the faces and viscoelastic honeycomb cells for the core. The Boltzmann superposition integral with the constant bulk modulus is used for modeling the viscoelastic material. The shear effect is expressed using the first-order shear deformation theory. The displacement field is predicted by the product of a determinate geometrical function and an indeterminate time function. The simple HP cloud mesh-free method is utilized for discretizing the equations in the space domain. Two coefficients of the time function are extracted by answering the equilibrium equation at two asymptotic times. And the last coefficient is easily determined by solving the first-order linear equation. Numerical results are presented to consider the effects of geometrical properties on the displacement history of viscoelastic honeycomb sandwich plates.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.1
• /
• pp.173-180
• /
• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

• Journal of Environmental Health Sciences
• /
• v.9 no.1
• /
• pp.15-30
• /
• 1983

The stochastic analysis was carried out to the hourly time series observed at Dae-gu, Wha-Myung and Ku-Mee in order to see water quality variation of the Nack-Dong River during Three months (July, Aug. and Sept.) in each year of 1979 and 1981. As a result of this study, it was found that 1. The simple correlation coefficients between some of the variables were fairly high. For example, the coefficients between Do and WT. were -0.824 (Dae-gu), -0.547 (Wha-myung), and -0.911(Ku-mee). The coefficients between COND and DO. were -0.263(Dae-gu), -0.347(Wha-myung) and -0.881 (Ku-mee). The coefficients between COND and WT. were 0.531 (Dae-gu), 0.361 (Wha-myung) and 0.800 (Ku-mee). 2. Hourly water quality time series of WT and DO existed as dominant 24 hours Periodicity For example, the Aut correlation coefficients about WT were 0.960 (K=1), 0.846(K=24), 0.691(K=48), 0.596(K=72), and 0.453(K=96). The auto-correlation coefficients of Do were 0.968 (K=1), 0.591 (K=24), 0.393 (K=48), 0.349 (K=72) and 0.250 (K=96). 3. Weekly water quality time series of WT and Do varied with the dominant 24 hours periodicity.

• Korean Management Science Review
• /
• v.32 no.2
• /
• pp.69-78
• /
• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• Journal of Soil and Groundwater Environment
• /
• v.19 no.4
• /
• pp.12-22
• /
• 2014

This study evaluated the pattern of groundwater fluctuation in cyrstalline rock using time series and factor analyses. From the results, groundwater level for the 18 wells was classified into 4 types reflecting the hydrogeological properties and rainfall event. Type 1 (DB1-5, DB1-6, DB2-2, KB-10, KB-13) was significantly influenced by groundwater flow through water-conducting features, whereas type 2 (DB1-3, DB1-7, KB-1~KB-3, KB-7, KB-11, KB-14, KB-15) was affected by minor fracture network as well as rainfall event. Type 3 (DB1-1, DB1-2) was mainly influenced by surface infiltration of rainfall event. Type 4 (DB1-8, KB-9) was reflected by the irregular variation of groundwater level caused by anisotropy and heterogeneity of crystalline rock.