• Earthquakes and Structures
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• 제16권2호
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• pp.165-175
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• 2019

Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

• 대한조선학회논문집
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• 제45권1호
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• pp.29-41
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• 2008

The present paper provides a CFD analysis of diffraction problem for a ship with forward speed using an unsteady RANS simulation method, a WAVIS code. The WAVIS viscous solver adopting a finite volume method has second order accuracy in time and field discretizaions for the RANS equations. A two phase level-set method and a realizable ${\kappa}-{\varepsilon}$ turbulence model are adopted to compute the free surface and to meet the turbulence closure, respectively. To validate the capability of the present numerical methods for the simulation of an unsteady progressive regular wave, computations are performed for three grid sets with refinement ratio of ${\sqrt{2}}$. The main simulation is performed for a DTMB5512 model with a forward speed in a regular head sea condition. Validation of the present numerical method is carried out by comparing the present CFD results with available unsteady experimental data published in the 2005 Tokyo CFD Workshop: resistance, heave force, pitch moment, unsteady free surface elevations and velocity fields.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.521-524
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• 2002

This paper deals with the rule generation from data for control system and data mining using rough set. If the cores and reducts are searched for without consideration of the frequency of data belonging to the same equivalent class, the unnecessary attributes may not be discarded, and the resultant rules don't represent well the characteristics of the data. To improve this, we handle the inconsistent data with a probability measure defined by support, As a result the effect of uncertainty in knowledge reduction can be reduced to some extent. Also we construct the rule base in a hierarchical structure by applying core as the classification criteria at each level. If more than one core exist, the coverage degree is used to select an appropriate one among then to increase the classification rate. The proposed method gives more proper and effective rule base in compatibility and size. For some data mining example the simulations are performed to show the effectiveness of the proposed method.

• 한국산학기술학회논문지
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• 제12권8호
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• pp.3430-3438
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• 2011

본 연구는 감귤의 소비자 선호도 조사를 통하여 객관적인 품질기준을 제시하는데 있다. 지금까지 제주 감귤의 품질 등급은 선과기를 이용한 크기에 따른 상품 구별과, 농 감협과 일부 영농 법인에서 비파괴 선과기를 이용하여 선별되어진 감귤을 자체적인 브랜드에 준하여 등급을 제시하여 왔다. 그 등급 설정은 과학적 객관적이거나, 소비자의 니즈에 의한 것이 아니라 편의에 위한 관행적 등급으로 판단된다. 그 등급 내용을 보면 최고등급 브랜드인 경우 당도 $12^{\circ}Bx$ 이상, 산도 1% 미만을 요구하고, 다음 등급 브랜드인 경우는 당도 $11^{\circ}Bx$, 산도 1% 미만을 요구하는 등 높은 당도와 낮은 산도를 천편일률적으로 적용하여 사용되어지고 있다. 따라서 감귤의 소비자 선호도 조사를 통한 소비자 만족도에 근거하여 당도 4등급, 산도 4등급으로 총 16개 등급으로 구분하였고, 이를 바탕으로 1등급에서 5등급까지의 5개의 등급을 설정하였다.

• 한국산학기술학회논문지
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• 제12권7호
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• pp.2996-3005
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• 2011

본 연구는 한라봉의 소비자 선호도 조사를 통하여 객관적인 품질등급 기준을 설정하는데 있다. 지금까지 한라봉의 품질등급은 선과기를 이용한 크기에 따른 상품 구별과, 농 감협과 일부 영농 법인에서 비파괴 선과기를 이용하여 선별되어진 자체적인 브랜드에 준하여 품질등급을 제시하여 왔다. 그 등급 설정은 과학적 객관적이거나, 소비자의 니즈에 의한 것이 아니라 편의에 위한 관행적 등급으로 판단된다. 그 등급 내용을 보면 당도 $13^{\circ}Bx$ 이상, 산1.0% 이하로 일률적으로 적용하여 사용되어지고 있다. 따라서, 본 연구에서는 한라봉의 소비자 선호도 조사를 통한 소비자 만족도에 근거하여 당도 5등급, 산도 7등급으로 총 35개 등급으로 구분하였다. 이를 바탕으로 1등급에서 5등급까지의 5개의 등급을 설정하고 상품(1~3등급)과 비상품(4~5등급)으로 구분하였다.

• The Journal of Asian Finance, Economics and Business
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• 제7권2호
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.327-332
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• 2005

We investigatea new fuzzy-neural networks-Hybrid Fuzzy set based polynomial Neural Networks (HFSPNN). These networks consist of genetically optimized multi-layer with two kinds of heterogeneous neurons thatare fuzzy set based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology to determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (namely gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is quantified through experimentation where we use a number of modeling benchmarks synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• 전자공학회논문지B
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• 제30B권9호
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• pp.1-8
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• 1993

In this paper, a new approach to the minimization of two-level Reed-Muller circuits is presented. In contrast to the previous method of using Xlinking operations to join two cubes for minimization. Cube selection method tries to select cubes one at a time until they cover the ON-set of the given function. A simple heuristic for selecting appropriate cubes is presented. In this heuristic, simply all cubes from the largest to the smallest are tried and whenever they decrease the number of remaining terms they are accepted. Since cubes once selected are not considered for a new selection, our method takes less time than other methods that need repetitive optimization process. The experimental results turned out to be improved in many cases compared to the best results in the literature.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2002년도 제1차워크샵
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• pp.139-152
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• 2002

Gene-shaving(Hastie et al, 2000) is a very useful method to identify a meaningful group of genes when the variation of expression is large. By shaving off the low-correlated genes with the leading principal component, the primary genes with the coherent expression pattern can be identified. Gene-shaving method works well If expression levels are varied enough, but it may not catch the meaningful cluster in low expression level or different expression time even with coherent patterns. The sliding window gene-shaving method which is to apply gene-shaving in each sliding window after hierarchical clustering is to compensate losing a meaningful set of genes whose variation is not large but distinct. The performance to identify expression patterns is compared for the simulated profile data by the different variance and expression level.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 F
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• pp.1937-1939
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• 1998

This paper presents a simple switching method to generate a PWM pattern mostly relevant to signle-phase three-level PWM rectifier. The adopted PWM switching pattern is performed in a manner similar to the space vector PWM method, which is popularly used in the three-phase rectifier and inverter. A set of possible voltages has been selected so that an equation with a time integral considered within a sampling period should be satisfied every sampling time. The simulation result shows that the proposed control scheme is good in some performance criteria such as unity power factor, low harmonic distortion of input current, dynamic response and voltage balancing of two series-connected DC capacitors.