• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.453-458
• /
• 1998

In this paper, a new approach to modeling of nonlinear systems using fuzzy theory is presented. So as to handle a variety of nonlinearity and reflect the degree of confidence in the informations about system, we combine multiple model method with hierarchical prioritized structure. The mountain clustering technique is used in partition of system, and TSK rule structure is adopted to form the fuzzy rules. Back propagation algorithm is used for learning parameters in the rules. Computer simulations are performed to verify the effectiveness of the proposed method. It is useful for the treatment fo the nonlinear system of which the quantitative math-approach is difficult.

• ETRI Journal
• /
• v.5 no.2
• /
• pp.17-28
• /
• 1983

This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.5
• /
• pp.512-519
• /
• 2003

In this paper, we propose a neuro-fuzzy modeling to improve the performance using the hierarchical clustering and Gaussian Mixture Model(GMM). The hierarchical clustering algorithm has a property of producing unique parameters for the given data because it does not use the object function to perform the clustering. After optimizing the obtained parameters using the GMM, we apply them as initial parameters for Adaptive Network-based Fuzzy Inference System. Here, the number of fuzzy rules becomes to the cluster numbers. From this, we can improve the performance index and reduce the number of rules simultaneously. The proposed method is verified by applying to a neuro-fuzzy modeling for Box-Jenkins s gas furnace data and Sugeno's nonlinear system, which yields better results than previous oiles.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.8
• /
• pp.2016-2025
• /
• 1994

A hierarchical planning strategy for dextrous manipulation of multifingered hands with soft finger contact model is proposed. Dextrous manipulation planning can be divided into a high-level stage which specifies the position/orientation trajectories of the fingertips on the object and a low-level stage which determines the contact forces and joint trajectories for the fingers. In the low-level stage, various nonlinear optimization problems are formulated according to the contact modes and integrated into a manipulation planning algorithm to find contact forces and joint velocities at each time step. Montana's contact equations are used for the high-level planning. Quasi-static simulation results are presented and illustrated by employing a three-fingered hand manipulating a sphere to demonstrate the validity of the proposed low-level planning strategy.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.120-122
• /
• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• Structural Engineering and Mechanics
• /
• v.30 no.5
• /
• pp.619-645
• /
• 2008

This study presents the efficiency of simulating structural systems using a method that combines a simplified component model (SCM) and rigorous component model (RCM). To achieve a realistic simulation of structural systems, a numerical model must be adequately capturing the detailed behaviors of real systems at various scales. However, capturing all details represented within an entire structural system by very fine meshes is practically impossible due to technological limitations on computational engineering. Therefore, this research develops an approach to simulate large-scale structural systems that combines a simplified global model with multiple detailed component models adjusted to various scales. Each correlated multi-scale simulation model is linked to others using a multi-level hierarchical modeling simulation method. Simulations are performed using nonlinear finite element analysis. The proposed method is applied in an analysis of a simple reinforced concrete structure and the Reuipu Elementary School (an existing structure), with analysis results then compared to actual onsite observations. The proposed method obtained results very close to onsite observations, indicating the efficiency of the proposed model in simulating structural system behavior.

• MALSORI
• /
• no.33_34
• /
• pp.71-89
• /
• 1997

In the framework of linear representation which allows for no internal structure within features, there is no way to represent nonlinear phonological phenomena such as complex segments. This paper shows how we carl solve some problems of the linear feature theory in relation to the hierarchical feature theory. The purpose of this paper is to explain lateral assimilation under hierarchical feature representation. Although arguments for the position of classes of distinctive features have been made the position of (lateral) remains the issue of debate. Sagey(1988) argues that the feature [lateral] is structurally dependent on the root node. In contrast Rice & Avery (1991) put the feature (lated) under the spontaneous voicing. I have discussed previous studies of feature hierarchy and I propose a revised model of feature representation. Within this model I have shown how well feature geometry describes lateralization as feature spreading.

• 한국방재학회:학술대회논문집
• /
• 2007.02a
• /
• pp.163-167
• /
• 2007

For numerical analysis of a tidal flow, a two-dimensional hydrodynamic model is developed by solving the nonlinear shallow-water equations. The governing equations are discretized explicitly with a finite difference leap-frog scheme and a first-order upwind scheme on adaptive hierarchical quadtree grids. The developed model is verified by applying to prediction of tidal behaviors. The calculated tidal levels are compared to available field measurements. A very reasonable agreement is observed.

• International Journal of Aeronautical and Space Sciences
• /
• v.16 no.3
• /
• pp.394-406
• /
• 2015

In this work, an efficient aircraft landing simulation strategy is proposed to develop an efficient and reliable hard-landing monitoring procedure. Landing stage is the most dangerous moment during operation cycle of aircraft and it may cause structural damage when hard-landing occurs. Therefore, the occurrence of hard-landing should be reported accurately to guarantee the structural integrity of aircraft. In order to accurately determine whether hard-landing occurs or not from given landing conditions, full nonlinear structural dynamic simulation can be performed, but this approach is highly time-consuming. Thus, a more efficient approach for aircraft landing simulation which uses a hierarchical aircraft landing model and an extended inertia relief technique is proposed. The proposed aircraft landing model is composed of a multi-body dynamics model equipped with landing gear and tire models to extract the impact force and inertia force at touch-down and a linear dynamic structural model with an extended inertia relief method to analyze the structural response subject to the prescribed rigid body motion and the forces extracted from the multi-body dynamics model. The numerical examples show the efficiency and practical advantages of the proposed landing model as an essential component of aircraft hard-landing monitoring procedure.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.4
• /
• pp.1013-1025
• /
• 2016

The purpose of this study was to analyze longitudinal effect of physical education activity (PEA) score on self-rated health evaluation change (SHEC). This study used hierarchical linear and nonlinear models to investigate of the SHEC during the transition into adolescence (from middle school 1st to high school 2nd grade). Using the Korea children and youth panel survey (KCYPA), data were collected over the course of five years (from 2010 and 2014). HLM 6.8 computer program was used to analyze the data. The result were as follows. First, boys' SHEC increased across the five years, and girls' SHEC decreased across the five years. Second, boys' the self-rated health was increased across the three years and decreased across the two years. Third, girls' the self-rated health was increased across the two years and decreased across the three years. Fourth, the PEA score of 1st grade of high school showed a significant positive association with the boys' SHEC. Fifth, the PEA score of 1st grade of middle school showed a significant negative association with the girls' SHEC.