• 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.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2009년도 춘계학술대회
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• pp.213-224
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• 2009

The present management of the domestic and international advanced enterprises is transferring the systems and the regulations to the prevention system management. Expecially, KOSHA (Korea Occupational Safety & Health Agency) in Korea has supported to set up the OSHMS (Occupational Safety & Health Management System) by KOSHA 18001 since 1997. But small & medium enterprises (SMS) has many difficulties to set up the OSHMS system because of limited natural and human resources. In this study, the rating system as a judgment method of an OSHMS based on the certification standard of the OSHMS was suggested for SMS to adopt voluntarily the OSHMS, certify KOSHA 18001, and improve the safety and health level.

• 한국소음진동공학회논문집
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• 제18권5호
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• pp.503-508
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• 2008

In this paper, various methods to improve the planetary gear noise in vehicles were introduced. Those cases of improvement have been used as good guidelines and references to prevent planetary noise problems. In this research, different types of planetary gear systems were also analyzed. The consequences of those analysis said in common that the planetary gear set generating noise mainly is the one which takes power directly from the turbine. Furthermore, a frequency versus vibration level map was introduced to judge how to solve the noise problem quickly in a vehicle development process. Besides, it is provided a predicting method which planetary gear set most contributes to noise problem taking in the vehicle and how to design the planetary gear set robustly.

• 산업경영시스템학회지
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• 제12권20호
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• pp.97-104
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• 1989

본 연구는 계층구조를 갖는 시스템의 각 목적함수들에 퍼지(FUZZY)집합 개념을 적용한 이단계 선형계획 모형을 다목적계획법으로 다루었다. 선형멤버쉽 함수를 이용하여 전형적인 Bi-level Linear Programming Problem(BLPP)으로 변형시켰으며, 기존의 BLPP 해법을 이용한 변형된 해법을 주시하고 예제를 통한 계산결과를 제시하였다. 퍼지이단계선형계층 (FBLPP)은 BLPP보다 실제환경을 자연스럽게 묘사할 수 있다. FBLPP는 각 의사결정자가 다목적함수를 갖는 다목적 이단계수리계획 모형의 유효해를 구하는데 이용할 수 있다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.201-206
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• 2005

In order to realistically represent the complex turbulence-chemistry interaction at the partially premixed turbulent lifted flames encountered in the gas turbine combustors, the combined conserved-scalar/level-set flamelet approach has been adopted. The parallel unstructured-grid finite-volume method has been developed to maintain the geometric flexibility and computational efficiency for the solution of the physically and geometrically complex flows. Special emphasis is given to the swirl effects on the combustion characteristics of the lean-premixed gas turbine combustor. Numerical results suggest that the present approach is capable of realistically simulating the combustion characteristics for the lean-premixed gas turbine engines and the lifted turbulent jet flame with a vitiated coflow.

• 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.

• Journal of Ship and Ocean Technology
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• 제10권4호
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• pp.1-11
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• 2006

The finite volume based multi-block RANS code, WAVIS developed at MOERI is applied to the numerical self-propulsion test. WAVIS uses the cell-centered finite volume method for discretization of the governing equations. The realizable $k-{\epsilon}$ turbulence model with a wall function is employed for the turbulence closure. The free surface is captured with the two-phase level set method and body forces are used to model the effects of a propeller without resolving the detail blade flow. The propeller forces are obtained using an unsteady lifting surface method based on potential flow theory. The numerical procedure followed the self-propulsion model experiment based on the 1978 ITTC performance prediction method. The self-propulsion point is obtained iteratively through balancing the propeller thrust, the ship hull resistance and towing force that is correction for Reynolds number difference between the model and full scale. The unsteady lifting surface code is also iterated until the propeller induced velocity is converged in order to obtain the propeller force. The self-propulsion characteristics such as thrust deduction, wake fraction, propeller efficiency, and hull efficiency are compared with the experimental data of the practical container ship. The present paper shows that hybrid RANS and potential flow based numerical method is promising to predict the self-propulsion parameters of practical ships as a useful tool for the hull form and propeller design.

• 대한조선학회논문집
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• 제46권3호
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• pp.219-231
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• 2009

Numerical simulations have been carried out for a 138K LNG Carrier (KLNG) model ship with free surface, using WAVIS 2.0 and Fluent 6.3.26 with various $y^+$ values and different grid densities. Level-set method for free surface capturing was adopted in WAVIS, while VOF has been used in Fluent. The calculated results were compared with the experiment data. Resistance coefficient, wave pattern, wave profile along the hull surface, axial velocity contours and transverse vectors had been analyzed. When the first $y^+$ value was fixed at 60, the simulation results from both WAVIS and Fluent were improved as the number of grids increased. The convergence time of WAVIS was much shorter than that of Fluent. Furthermore, WAVIS predicted the velocity field and the wave profile along the hull surface better than Fluent. However, Fluent gave better wave patterns.

• 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.