• Journal of the Korean Data and Information Science Society
• /
• v.23 no.4
• /
• pp.825-832
• /
• 2012

We propose a novel way of forecasting the market shares of several brands simultaneously in a multiplicative competitive interaction model, which uses kernel regression technique incorporated with kernel machine technique applied in support vector machines and other machine learning techniques. Traditionally, the estimations of the market share attraction model are performed via a maximum likelihood estimation procedure under the assumption that the data are drawn from a normal distribution. The proposed method is shown to be a good candidate for forecasting method of the market share attraction model when normal distribution is not assumed. We apply the proposed method to forecast the market shares of 4 Korean car brands simultaneously and represent better performances than maximum likelihood estimation procedure.

• Journal of Korean Society for Quality Management
• /
• v.30 no.4
• /
• pp.68-77
• /
• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.29 no.3
• /
• pp.163-174
• /
• 2023

Though box compression strength (BCS) is commonly used as a performance criterion for shipping containers, estimating BCS remains a challenge. In this study, artificial neural networks (ANN) are implemented as a new tool, with a focus on building up ANN architectures for BCS estimation. An Artificial Neural Network (ANN) model can be constructed by adjusting four modeling factors: hidden neuron numbers, epochs, number of modeling cycles, and number of data points. The four factors interact with each other to influence model accuracy and can be optimized by minimizing model's Mean Squared Error (MSE). Using both data from the literature and "synthetic" data based on the McKee equation, we find that model estimation accuracy remains limited due to the uncertainty in both the input parameters and the ANN process itself. The population size to build an ANN model has been identified based on different data sets. This study provides a methodology guide for future research exploring the applicability of ANN to address problems and answer questions in the corrugated industry.

• Journal of the Korea Convergence Society
• /
• v.8 no.10
• /
• pp.37-43
• /
• 2017

In this paper, we propose a method for estimation software quality in terms of software test data, and it is necessary to predict the period of time required for software test evaluation. We need a model to understand of estimation of software quality. In this paper, we propose a model to estimate the number of days for software test using the data obtained through the tester's sex, and present a model for analysing the number of errors according to six quality characteristics by software type.

• Journal of information and communication convergence engineering
• /
• v.5 no.4
• /
• pp.295-299
• /
• 2007

This paper presents the ASF(Additional Secondary Factor) modeling of DGPS beacon signal. In addition to DGPS's original purpose, the feasibility to utilize DGPS system for timing and navigation has been studied. For timing and navigation, the positioning system must know the accurate time delay of signal traveling from the transmitter to receiver. Then the delay can be used to compute the user position. The DGPS beacon signal transmits the data using medium frequency, which travels through the surface and cause the additional delay rather than the speed of light according to conductivities and elevations of the irregular terrain. We introduce the modeling of additional delay(ASF) and present the results of implementation. The similar approach is Locan-C. Loran-C has been widely used as the maritime location system and was enhanced to E-Loran(Enhanced Loran). E-Loran system uses the ASF estimation method and is able to provide the more precise location service. However there was rarely research on this area in Korea. Hence, we introduce the ASF and its estimation model. With the comparison of the same condition and data from the original Monteath model and ASF estimation data of Loran system respectively, we guarantee that the implementation is absolutely perfect. For further works, we're going to apply the ASF estimation model to Korean DGPS beacon system with the Korean terrain data.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.5
• /
• pp.104-114
• /
• 1996

For the improvement of productivity, the reduction of cost and time for manufacturing is mandatory, especially in the field of electromic industry. The study is concerned with a practical means of systematic assistance to formability estimation and selection of reliable design specification for electronic sheet metal parts. The objective of this research work is to develop a simulation system which hops to analyze the target processes with the finite element method and to acquire available design data quickly and exactly. The simulation system developed in the study consists of design verification, selection of optimal combination of parameters, knowledge acquisition and graphical user interface(GUI). Design verification is automatically carried out by using the finite element method. A data base management system and nomograms are utilized for knowledge acquisition. The developed system has been applied to some major sheet metal forming operations such as flanging, embossing, bending and blanking. According to the simulated results, the validation of the target processes has been confirmend. Analysis data, estimation rules of formability and graphical representation of the analysis have been employed for the designer's understanding and evaluation, thus providing a practical means of robust design and evaluation of forma- bility for producing electronic sheet metal parts.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.4
• /
• pp.755-762
• /
• 2013

In this paper we consider the NHPP software reliability model. And we deal with the maximum likelihood estimation and the Bayesian estimation with conjugate prior for parameter inference in the mean value function of Goel-Okumoto model (1979). The parameter estimates for the proposed model is presented by MLE and Bayes estimator in data set. We compare the predicted number of faults with the actual data set using the proposed mean value function.

• International Journal of Contents
• /
• v.14 no.2
• /
• pp.1-6
• /
• 2018

In a wireless mobile communication system, a pilot signal has been considered to be a necessary signal for estimating a changing channel between a base station and a terminal. All mobile communication systems developed so far have a specification for transmitting pilot signals. However, although the pilot signal transmission is easy to estimate the channel,(Ed: unclear wording: it is easy to use the pilot signal transmission to estimate the channel?) it should be minimized because it uses radio resources for data transmission. In this paper, we propose a pilotless channel estimation scheme (PCE) by introducing the clustering method of unsupervised learning used in our deep learning into channel estimation.(Ed: highlight- unclear) The PCE estimates the channel using only the data symbols without using the pilot signal at all. Also, to apply PCE to a real system, we evaluated the performance of PCE based on the resource block (RB), which is a resource allocation unit used in LTE. According to the results of this study, the PCE always provides a better mean square error (MSE) performance than the least square estimator using pilots, although it does not use the pilot signal at all. The MSE performance of the PCE is affected by the number of data symbols used and the frequency selectivity of the channel. In this paper, we provide simulation results considering various effects(Ed: unclear, clarify).

• Journal of Korean Society on Water Environment
• /
• v.28 no.2
• /
• pp.247-254
• /
• 2012

Soil and Water Assessment Tool (SWAT) model has been widely used in estimation of flow and water quality at various watersheds worldwide, and it has an auto-calibration tool that could calibrate the flow and water quality data automatically from thousands of simulations. However, only continuous measured day flow/water quality data could be used in the current SWAT auto-calibration tool. Therefore, 8-day interval flow and water quality data measured nationwide by Korean Ministry of Environment (MOE) could not be used in SWAT auto-calibration even though long-term flow and water quality data in the Korean Total Maximum Daily Load (TMDL) watersheds available. In this study, current SWAT auto-calibration was modified to calibrate flow and water quality using 8-day interval flow and water quality data. As a result of this study, the Nash and Sutcliffe Efficiency (NSE) values for flow estimation using auto-calibration are 0.77 (calibration period) and 0.68 (validation period), and NSE value for water quality (T-P load) estimation (using the 8-day interval water quality data) is 0.80. The enhanced SWAT auto-calibration could be used in the estimation of continuous flow and water quality data at the outlet of TMDL watersheds and ungaged point of watersheds. In the next study, the enhanced SWAT auto-calibration will be integrated with Web based Load Duration Curve (LDC) system, and it could be suggested as methods of appraisal of TMDL in South Korea.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.1
• /
• pp.55-63
• /
• 2019

In engineering problems, many random variables have correlation, and the correlation of input random variables has a great influence on reliability analysis results of the mechanical systems. However, correlated variables are often treated as independent variables or modeled by specific parametric joint distributions due to difficulty in modeling joint distributions. Especially, when there are insufficient correlated data, it becomes more difficult to correctly model the joint distribution. In this study, multivariate kernel density estimation with bounded data is proposed to estimate various types of joint distributions with highly nonlinearity. Since it combines given data with bounded data, which are generated from confidence intervals of uniform distribution parameters for given data, it is less sensitive to data quality and number of data. Thus, it yields conservative statistical modeling and reliability analysis results, and its performance is verified through statistical simulation and engineering examples.