• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.86-89
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• 2003

To model a numerical problem space under the limitation of available data, we need to extract sparse but key points from the space and to efficiently approximate the space with them. This study proposes a sampling method based on the search process of genetic algorithm and a space modeling method based on least-squares approximation using the summation of Gaussian functions. We conducted simulations to evaluate them for several kinds of problem spaces: DeJong's, Schaffer's, and our original one. We then compared the performance between our sampling method and sampling at regular intervals and that between our modeling method and modeling using a polynomial. The results showed that the error between a problem space and its model was the smallest for the combination of our sampling and modeling methods for many problem spaces when the number of samples was considerably small.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.148-160
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• 2009

By the development of recent technology, a new variant of rotorcrafts having four rotors start drawing attention from aerial-robotics engineers more than before. Its potential spans from just being control device test bed to performing difficult task such as carrying surveillance device to unreachable places. In this regards, modeling a quad-rotor is significant in analyzing its dynamic behavior and in synthesizing control system for such a vehicle. This paper summarizes the modeling of a mini quad-rotor aerial vehicle. A first principle approach is considered for deriving the model based on Euler-Newton equations of motion. The result of the modeling is a simulation platform that is expected to acceptably predict the dynamic behavior of the quad-rotor in various flight conditions. Linear models associated with different flight condition can be extracted for the purpose of control synthesis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.8 s.239
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• pp.1153-1160
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• 2005

Many methods of spot weld modeling have been developed to increase efficiency and guarantee the robustness fer the CAE analysis. In this research they are introduced and the performance is compared in a viewpoint of stiffness and durability. For evaluating the performance a multi-spot welded specimen as well as two single welded specimen is used. The results show that the CWELD element considering 'patch to patch' is stiffer than other modeling methods in stiffness and more conservative in durability. It also offers simple modeling and since it is much easier to maintain the orrhogonality of the BAR element expressing a nugget, we can obtain more exact reaction forces and moments in a nugget. Therefore the CWELD element is the most excellent in the assessment of durability.

• Journal of Magnetics
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• v.16 no.2
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• pp.114-119
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• 2011

This paper presents a magnetization modeling method combined with material sensitivity information to identify the unknown magnetization distribution of a hull and improve the accuracy of the predicted fields. First, based on the magnetization modeling, the hull surface was divided into three-dimensional sheet elements, where the individual remanent magnetization was assumed to be constant. For a fast search of the optimum magnetization distribution on the hull, a material sensitivity formula containing the first-order gradient information of an objective function was combined with the magnetization modeling method. The feature of the proposed method is that it can provide a stable and accurate field solution, even in the vicinity of the hull. Finally, the validity of the method was tested using a scale model ship.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.142-149
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• 2000

Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event simulation and continuous is provoked, resulting in a combined discrete-continuous simulation. Continuous simulation concerns the modeling over time of a system by a representation in which the state variables change continuously with respect to time. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which presents the equation of continuous part in supply chain and how these equations are used supply chain simulation models. A simple supply chain model is demonstrated the possibility and the capability of this approach.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.112-116
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• 2008

This paper presents URS (Ubiquitous Robotic Space) Modeling and service technique for the robotic security service while bridging between virtual space and physical space. First, this paper introduces a concept of virtual URS and responsive virtual URS. Second, this paper addresses modeling of URS which covers modeling of indoor geometry and environment sensor. Third, this paper describes virtual URS services including interactive virual-physical bridging service.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.235-238
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• 2010

Since the mid 1990s airborne LiDAR data have been widely used, automation of building modeling is getting a central issue. LiDAR data processing for building modeling is involved with extracting surface patch elements by segmentation and surface fitting with optimal mathematical functions. In this study, simulation LiDAR data were generated with complex polyhedral roofs of buildings and an automatic modeling approach was proposed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.87-94
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• 2017

Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.

• Journal of the Korean School Mathematics Society
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• v.22 no.2
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• pp.133-161
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• 2019

In this paper, we analyzed the case of supporting the mathematical modeling activities through the group creativity in everyday class of 9th grade. The details are as follows. First, through the theoretical review, the meaning of group creativity according to sociocultural perspective and the sociocultural characteristics of mathematical modeling were confirmed. Second, we experimented in a classroom consisting of 5 groups of 4 students, and conducted a case study focusing on a well developed group of group creativity. The results are as follows. First, group creativity with various types of interaction and creativity synergy was observed at each stage of mathematical modeling. According to the stag e of mathematical modeling and the type of interaction, different creative synergy was developed. Second, the developed group creativity supported each step of mathematical modeling. According to the stage of mathematical modeling and the type of interaction, group creativity supported mathematical modeling activities in different directions.