• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2006년도 춘계학술논문 발표대회 제6권1호
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• pp.119-124
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• 2006

Design-Build, one contractor is responsible for both the design and construction, has become more popular since the government framed the policy on how to activate the design-build projects in 1996. The reality is, however, there are many problems encounted on Contractor Selection Method for Public Design-Build Projects. The purpose of this paper is to improve the problems, no way to meet the goal(value) the owners expect from the design-build projects, for instance, not fully reflecting the characteristics of projects and owners intention, not systematical enough to judge if bidders could carry out the contract. This study will insist we introduce Best Value Procurement, which is being commonly used in some advanced countries recently, so that we would properly select the contractor suitable for Best Value concept which totally depends on the owners, types of work and specified conditions. Furthermore, by passing through the Two-Step Procedures following Pre-qualification in Best Value Procurement, we expect it lighten the bidders' burden for proposal and the owners' complicate bid administration.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.516-525
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• 2005

Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권9호
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• pp.920-926
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• 2005

최근접 이웃(k nearest neighbor) 알고리즘은 새로운 개체의 목표값을 예측하기 위하여 과거의 유사한 데이타를 이용하여 그 값을 예측하는 것이다. 이 방법은 기계학습의 여러 분야에서 그 유용성을 검증받아 널리 사용되고 있다. 이러한 kNN 알고리즘에서 목표값을 예측할 때 각 속성의 가중치를 동일하게 고려하는 것은 좋은 성능을 보장할 수 없으며 따라서 kNN에서 각 속성에 대한 가중치를 적절히 계산하는 것은 kNN 알고리즘의 성능을 결정하는 중요한 요소중의 하나이다. 본 논문에서는 정보이론을 이용하여 kNN 에서의 속성의 가중치를 효과적으로 계산하는 새로운 방법을 제시하고자한다. 제안된 방법은 각 속성이 목표 속성에 제공하는 정보의 양에 따라 가중치를 자동으로 계산하여 kNN 방법의 성능을 향상시킨다. 개발된 알고리즘은 다수의 실험 데이타를 이용하여 그 성능을 비교하였다.

• 정보처리학회논문지B
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• 제16B권3호
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• pp.233-238
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• 2009

자질 수가 적은 소규모 크기 문서들의 자동분류는 좋은 성능을 얻기 어렵다. 그 이유는 문서집단 전체의 자질 수는 크지만 단위 문서 내 자질 수가 상대적으로 너무 적기 때문에 문서간 유사도가 너무 낮아 우수한 분류 알고리즘을 적용해도 좋은 성능을 얻지 못한다. 특히 웹 디렉토리 문서들의 자동분류에서나, 디스크 복구 작업에서 유사도 평가와 자동분류로 연결되지 않은 섹터를 연결하는 작업에서와 같은 소규모 크기 문서의 자동분류에서는 좋은 성능을 얻지 못한다. 따라서 본 논문에서는 소규모 크기 문서의 자동분류에서의 문제점을 해결하기 위해 분류 사전작업으로, 예제기반 자질 필터링 방법 Relief-F알고리즘을 소규모 문서 내 자질 필터링에 적합한 ERelief-F 알고리즘을 제시한다. 또 비교 실험을 위해, 기존의 자질 필터링 방법 중 Odds Ratio와 정보이득, 또 Relief-F 알고리즘을 함께 실험하여 분류결과를 비교하였다. 그 결과, ERelief-F 알고리즘을 사용했을 때의 결과가 정보이득과 Odds Ratio, Relief-F보다 월등히 우수한 성능을 보였고 부적절한 자질도 많이 줄일 수 있었다.

• 한국식품조리과학회지
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• 제29권5호
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• pp.553-562
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• 2013

The purpose of this study was to analyze the key factors considered important by customers in the selection of a Korean restaurant through the use of conjoint analysis techniques. A total of 400 questionnaires were distributed over a 2-week period in October 2011, of which 354 were completed (88.5%). Statistical analysis was then carried out using the Windows 18.0 Statistics package. The research was based on the analysis of two target areas - daily meals and special purpose meals. Responses were measured by using Zaichkowsky's Personal Involvement Inventory (PII) and a 7-point Likert Scale. Overall it was found that in all areas of the results regarding the involvement related analyses, daily meals scored lower than special purpose meals. This implied that the choice of daily meals is more applicable to customers with a low level of involvement, whereas high-involvement customers were more likely to focus on special purpose meals. The analysis of high-involvement customers revealed that the quality of food, price, service quality and physical environment, in order of priority, were the most important factors in selecting a restaurant. The use of the optimum attribute combination revealed the following results: delicious food (0.601); friendly staff (0.170); clean restaurant (0.191); price of 20,000 won (-0.513). Furthermore, low-involvement customers considered the following factors as important when selecting a Korean restaurant: quality of food, followed by price, physical environment and service quality in that order. In this instance, the optimum attribute combination showed the following outcomes: tasty food (0.645); friendly staff (0.418); clean restaurant (0.365); price of 5,000 won (-0.847). These results indicated the importance of developing a marketing plan which was based specifically on a customer's involvement level, focusing on their main selection criteria when choosing a Korean restaurant.

• 한국경영과학회지
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• 제25권3호
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• pp.109-124
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• 2000

For rational human value judgement and evaluation, provision of clear evaluation data, objective value judgement criteria, and properly generalized methods are required. For instance, this is true for software quality evaluation, and the measure of software quality and the weighting method of evaluation target directly affect final decisions. However it is not easy to find a generalized method for the software quality evaluation or product selection, because of its complex characteristics. In this paper, we apply the qualitative preference method based on quantitative belief functions to find a general weighing method for the software quality evaluation. In particular, the qualitative preference method, in which the differentiated preference expression is possible, is conceptually expanded for general applications in future. For this purpose, we hierarchically differentiate the strong preference relation from the weak preference relation, and show an example of quantification of software quality evaluation on different applications, by comparing the qualitative preference method with AHP. We believe that the application domain of this method is not limited to the software quality evaluation and it is very useful to apply this results to other SE areas, e.g., metric selection with different views and riority determination of practices to be assessed in the SPICE.

• JSTS:Journal of Semiconductor Technology and Science
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• 제15권5호
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• pp.437-444
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• 2015

In simulation-based circuit optimization, many simulation runs may be wasted while evaluating infeasible designs, i.e. the designs that do not meet the constraints. To avoid such a waste, this paper investigates the use of support vector machine (SVM) classifiers in predicting the design's feasibility prior to simulation and the optimal selection of the SVM parameters, namely, the Gaussian kernel shape parameter ${\gamma}$ and the misclassification penalty parameter C. These parameters affect the complexity as well as the accuracy of the model that SVM represents. For instance, the higher ${\gamma}$ is good for detailed modeling and the higher C is good for rejecting noise in the training set. However, our empirical study shows that a low ${\gamma}$ value is preferable due to the high spatial correlation among the circuit design candidates while C has negligible impacts due to the smooth and clean constraint boundaries of most circuit designs. The experimental results with an LC-tank oscillator example show that an optimal selection of these parameters can improve the prediction accuracy from 80 to 98% and model complexity by $10{\times}$.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2002년도 11월 학술대회지
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• pp.209-213
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• 2002

This paper describes the reduction of DB without degradation of speech quality in Corpus-based Speech synthesizer of Korean language. In this paper, it is proposed that the frequency of every unit in reduced DB should reflect the frequency of units in Korean language. So, the target population of every unit is set to be proportional to their frequency in Korean large corpus(780K sentences, 45Mega phonemes). Second, the frequent instances during synthesis should be also maintained in reduced DB. To the last, it is proposed that frequency of every instance should be reflected in clustering criterion and used as criterion for selection of representative instances. The evaluation result with proposed methods reveals better quality than using conventional methods.

• 한국생활과학회지
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• 제9권1호
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• pp.63-70
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• 2000

The purpose of this study is The results was that consumers who like to the top brand's commodities, had commonly high tendency to and fro its trademark and store allegiance. Furthermore, they have usually bought something following on their inclination what they had purchased as well as the store decoration character and the marketing promotion attribute. The other consumers who prefer to the discount store's merchandises, had also high propensity and the biggest influence on buying something which were those factors; their instance shopping habit, utility-economy trait, follow the fashion character and strong circumspection tendency besides using the mass media Info., personal data and commodities' attribute.

• 대한음성학회지:말소리
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• 제44호
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• pp.145-156
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• 2002

This paper describes the reduction of DB without degradation of speech quality in Corpus-based Speech synthesizer of the Korean language. In this paper, it is proposed that the frequency of every unit in reduced DB reflect the frequency of units in the Korean language. So, the target population of every unit is set to be proportional to its frequency in Korean large corpus (780k sentences, 45Mega phones). Secondly, the frequent instances during synthesis should be also maintained in reduced DB. To the last, it is proposed that frequency of every instance be reflected in clustering criteria and used as another important criterion for selection of representative instances. The evaluation result with proposed methods reveals better quality than that using conventional methods.