• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.33-49
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• 2000

This research demonstrates the application of GIS to the selection of the waste landfill site through the case study of a urban area. The estimation factors for the suitability analysis of the waste landfill site were determined. The database was built through collection, input, and transformation of data. The recent land cover classification data and NDVI data which were obtained through processing of satellite imagery were incorporated into GIS data as estimation factors. The relative weights of importance among 2nd category estimation factors were determined by the pairwise comparison method. Also relative weights of 1st category estimation factors which are divided into the social-economical factor and the natural environmental factor were combined with those of 2nd category estimation factors. As the results of this case study, the suitability analysis was conducted in accordance with various estimation criteria. The highest suitability index was obtained in the case where we considered the relative weights of 2nd category estimation factors as different in the viewpoint which regards the social economical factor as important.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1659-1662
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• 1997

The objective of this paper is to estimate the aerodynamic derivatives of a single turbo-prop aircraft at a specified flight condition for the best deduction of the dynamic characteristics using modified maximum likelihood estimation method whcih is known to be unbiased, efficient, and consistent. The flight test data necessary to the estimation of aerodynamic derivatives is obtained by implementing the six degree of freedom nonlinear flight simulation to consider the effects of several control input types, control deflection amplitudes, and intensity of turbulence. The simulated data is added with the measurement noise, which is regarded as the actual flight test data.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.4 s.19
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• pp.61-69
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• 2004

This paper presents a new analytical method for estimating the location of a target using directional data. Based on a nonlinear programming (NLP) problem formulated for the line method, which is a well known algorithm for two-dimensional location estimation, we present a method to find an optimal solution for the problem. Then we present a two-stage method for better location estimation based on the NLP problem. In addition, another two-stage method is presented for location estimation problems in which different types of observers are used to obtain directional data based on the analysis of the maximum likelihood estimate of the target location. The performance of the suggested method is evaluated through simulation experiments, and results show that the two-stage method is computationally efficient and highly accurate.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.903-924
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• 2000

This paper examines the alternative method to measure the state of overall economic activity. The macroeconomic variables, used for business cycle, take more than a month after a period for collection and aggregation. The electricity generation data is compiled in mechanical ways just after the period. Based on this fact, we develop the two stage estimation method for coincident economic indicators in order to detect the business cycle in an earlier period, using Stock-Watson's Dynamic Factor Model. Using monthly data from 1970 to 1999, it is found that the experimental coincidence economic indicators are well-fitted to data and also that the estimates of two stage estimation method have good explanatory power, equivalent to the experimental coincidence economic indicators. While the RMSE of coincidence economic indicators is found to be 1.27%, that of the experimental coincidence economic indicators is found to be 1.31% and that of the two stage estimation method is around 1.44%. If we take consideration into the fact that it measures the business cycle in one month earlier, we come to the conclusion that the two stage estimation is of great use.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.125-137
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• 2005

Many discriminant analysis models for binary data have been used in real applications, but none of the classification models dominates in all varying circumstances(Asparoukhov & Krzanowski(2001)). Lee and Hwang (2003) proposed a new classification model by using multinomial distribution with the maximum entropy estimation method. The model showed some promising results in case of small number of variables, but its performance was not satisfactory for large number of variables. This paper explores to use the iterative cross entropy minimization estimation method in replace of the maximum entropy estimation. Simulation experiments show that this method can compete with other well known existing classification models.

• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.1-11
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• 2015

The efficient safety estimation for a business should analyze an accident data by considering every possible and potential factor. Thus, we consider several factors to build the safety estimation model to meet fairness and rationality. This paper present the yearly statistic data of accident from KOSHA analyze the data by industry, scale, year of service of a employee, age and other factors; build the safety estimation model for the business based on the accident report derived the analysis. The estimation model is established by the weights for accident type, degree, scale, industry, year of service, and age of the employee derived from ANP(Analytic Network Process).

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.114-119
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• 2001

An expert system for estimation of fatigue properties from simple tensile data of material is developed, considering nearly all important estimation methods proposed so far, i.e., 7 estimation methods. The expert system is developed to utilize for the case of only hardness data available. The knowledge base is constructed with production rules and frames using an expert system shell, UNIK. Forward chaining is employed as a reasoning method. The expert system has three major functions including the function to update the knowledge base. The performance of the expert system is tested using the 54 $\varepsilon$-N curves consisting of 381 $\varepsilon$-N data points obtained for 22 materials. It is found that the expert system developed has excellent performance especially for steel materials, and reasonably good for aluminum alloys.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.157-167
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• 2006

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expects it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. These factors make the sales dynamic and unstable. In this paper we develop a time series model to evaluate the sales patterns with stockpiling and short-term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.1-7
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• 2010

The efficient safety estimation for a business should analyze an accident data by considering every possible and potential factor. Thus, we consider several factors to build the safety estimation model to meet fairness and rationality. This paper present the yearly statistic data of accident from KOSHA analyze the data by industry, scale, year of service of a employee, age and other factors; build the safety estimation model for the business based on the accident report derived the analysis. The estimation model is established by the weights for accident type, degree, scale, industry, year of service, and age of the employee derived from AHP(Analytic Hierarchy Process).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.171-178
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• 2017

This paper studies the state estimation problem for static neural networks with time-varying delay. Unlike other studies, the controller scheme, which involves time-varying sampling and uncertainties, is first employed to design the state estimator for delayed static neural networks. Based on Lyapunov functional approach and linear matrix inequality technique, the non-fragile sampled-data estimator is designed such that the resulting estimation error system is globally asymptotically stable with $H_{\infty}$ performance. Finally, the effectiveness of the developed results is demonstrated by a numerical example.