• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.276-279
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• 2005

A review of how the functions of two or more independent variables can be approximated by using fuzzy systems is provided in this paper. We start with an exact represention of a linear interpolation function of two independent variables by using a fuzzy system. Next, we describe how this function can be approximated by another fuzzy system with a lesser number or with a desired number of output fuzzy sets. Thus, a reduction of the storage needed is achieved by storing the fuzzy rules or equivalently the output fuzzy set numbers instead of storing the whole discrete function values. A description on how the cubic spl me interpolation function can be represented exactly by using the fuzzy system method is provided, along with a few examples where fuzzy rule tables with a size of 7$\times$7 provide a representation of the functions with relative errors of the order of $10^{2}$ or less.

• IE interfaces
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• v.11 no.3
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• pp.89-101
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• 1998

The randomness of the input variables in simulation experiments produce output responses which are also realizations of random variables. The random responses make necessary the use of statistical inferences to adequately describe the stochastic nature of the output. The analysis of the simulation output of non-terminating simulations is frequently complicated by the autocorrelation of the output data and the effect of the initial conditions that produces biased estimates. The regenerative method has been developed to deal with some of the problems created by the random nature of the simulation experiments. It provides a simple solution to some tactical problems and can produce valid statistical results. However, not all processes can he modeled using the regenerative method. Other processes modeled as regenerative may not return to a given demarcating state frequently enough to allow for adequate statistical analysis. This paper shows how the state transformation concept was successfully used in a queueing model and a job shop model. Although the first example can be analyzed using the regenerative method. it has the problem of too few recurrences under certain conditions. The second model has the problem of no recurrences. In both cases, the state transformation increase the frequency of the demarcating state. It was shown that time state transformations are regenerative and produce more cycles than the best typical discrete demarcating state in a given run length.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.77-91
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• 2007

In this paper, we present a symbiotic evolutionary algorithm for multi-objective optimization. The goal in multi-objective evolutionary algorithms (MOEAs) is to find a set of well-distributed solutions close to the true Pareto optimal solutions. Most of the existing MOEAs operate one population that consists of individuals representing the entire solution to the problem. The proposed algorithm has a two-leveled structure. The structure is intended to improve the capability of searching diverse and food solutions. At the lower level there exist several populations, each of which represents a partial solution to the entire problem, and at the upper level there is one population whose individuals represent the entire solutions to the problem. The parallel search with partial solutions at the lower level and the Integrated search with entire solutions at the upper level are carried out simultaneously. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The optimization problems with continuous variables and discrete variables are used as test-bed problems. The experimental results confirm the effectiveness of the proposed algorithm.

• Korean Chemical Engineering Research
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• v.48 no.4
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• pp.475-482
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• 2010

In this work, soft sensor based on image anlaysis is proposed for quantitatively estimating the visual appearance of manufactured products and is applied to quality monitoring. The methodology consists of three steps; (1) textural feature extraction from product images using wavelet transform, (2) numerical estimation of the product appearance through projection of the textural features on subspace, and (3) use of latent variables of textural features (i.e., numerical estimates of product appearance). The focus of this approach is on the consistent and quantitative estimation of continuous variations in visual appearance rather than on classification into discrete classes. This approach is illustrated through the application to the estimation and monitoring of the appearance of engineered stone countertops.

• Steel and Composite Structures
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• v.7 no.1
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• pp.53-70
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• 2007

This paper presents a analysis of the problem of optimal design of the beams with two I-type cross section shapes. These types of beams are simply supported and subject to pure bending. The strength and stability conditions were formulated and analytically solved in the form of mathematical equations. Both global and selected types of local stability forms were taken into account. The optimization problem was defined as bicriteria. The cross section area of the beam is the first objective function, while the deflection of the beam is the second. The geometric parameters of cross section were selected as the design variables. The set of constraints includes global and local stability conditions, the strength condition, and technological and constructional requirements in the form of geometric relations. The optimization problem was formulated and solved with the help of the Pareto concept of optimality. During the numerical calculations a set of optimal compromise solutions was generated. The numerical procedures include discrete and continuous sets of the design variables. Results of numerical analysis are presented in the form of tables, cross section outlines and diagrams. Results are discussed at the end of the work. These results may be useful for designers in optimal designing of thin-walled beams, increasing information required in the decision-making procedure.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.48-53
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• 1999

This paper presents an analytic derivation of the erroneous effect when the sliding-DFT is implemented in a recursive way with the finite-bit approximation of the twiddle factors. The analysis result is obtained in a closed form equation of the noise-to-signal power ratio(NSR) employing the zero-mean white Gaussian signal as the target input of the DFT. The parameters of the wordlength used in representing the twiddle factors and the blocklength of the DFT appear in the NSR explicitly as its function variables. The derivation is based on the error dynamic equation which is derived from the recursive SDFT, and on the analytic exploration of the statistical characteristics of the approximation coefficients treating them as random variables of having spatial distributions. The analytically derived results are verified through the comparison with the data actually measured from the computer simulation experiment.

• Korean Journal of Computational Design and Engineering
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• v.5 no.2
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1262-1269
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• 2005

Thrust of linear motor is one of the important factor to specify motor performance. Maximum thrust can be obtained by increasing the current in conductor and is relative to the sizes of conductor and magnet. But, the current and the size of conductor have an effect on temperature of linear motor. Therefore, it is practically important to find design results that can effectively maximize the thrust of linear motor within limited range of temperature. Finite element analysis was applied to calculate thrust and the temperature of the conductor was calculated by the thermal resistance. The diameter of copper wire among design variables has discrete value and number of turns must be integer. Considering these facts, special techinque for optimum design is presented. To reduce excessive computation time of thrust in optimization, the design variables was redefined by analysis of variance and second order regression model for thrust was determined by response surface metheodology. As a result, it is shown that the proposed method has an advantage in optimum design of linear motor.

• Publications of The Korean Astronomical Society
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• v.31 no.3
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• pp.43-56
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• 2016

Through time-series BV CCD photometry of the open cluster NGC 225 region, we have detected 30 variable stars including 22 new ones. They are five ${\delta}$ Scuti-type variable stars, a slowly pulsating B star, six eclipsing binary stars and 18 semi-long periodic or slow irregular variables, respectively. We have performed multiple-frequency analysis to determine pulsation frequencies of the ${\delta}$ Scuti-type stars and a slowly pulsating B star, using the discrete Fourier transform and linear least-square fitting methods. We also have derived the periods and amplitudes of 6 eclipsing binaries and a long-period variable star from the phase fitting method, and presented the light curves of all variable stars. A slowly pulsating B star is a member of NGC 225, but ${\delta}$ Scuti-type stars are not members from the positions in the color-magnitude diagram and the radial distancies from the center of the cluster. From Dias et al. (2014, A&A, 564, 79), only three variable stars including the slowly pulsating B star are members of clusters: two are in NGC 225 and one is in Stock 24. But a variable star in Stock 24 is not a member of the cluster because of its position of color-magnitude diagarm.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.6
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• pp.12-19
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• 2003

Corrugated bulkheads for a bulk carrier are divided into watertight bulkheads and deep tank bulkheads. Design of the watertight bulkheads is principally determined by the permissible limit of Classification and IACS requirements. But, the verification of strength through finite element analysis is indispensable for design of the deep tank bulkheads. A stage for stress evaluation of corrugated part is required for optimum structural design of the deep tank bulkheads. Since the finite element analysis for real model requires excessive amount of calculation time, in this study one corrugated structure is replaced with beam element and is idealized as 2 dimensional frame structure connected to upper and lower stool Minimum weight design of the deep tank bulkheads is performed through generalized sloped deflection method(GSDM) as direct calculation method. The purpose of this study is the development of design system for the minimization of steel weight of deep tank bulkheads as well as watertight bulkheads. Discrete variables are used as design variables for the practical design. Evolution strategies(ES) is used as an optimization technique.