• Communications for Statistical Applications and Methods
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• 제24권6호
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• pp.651-662
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• 2017

We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

• 한국CDE학회논문집
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• 제3권4호
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• pp.236-242
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• 1998

This paper presents a development of computer aided cutting tool selection techniques for rough and finish turning operations. The developed system,. which is one of important activities for computer aided operation planning, firstly implements operation sequencing. Then, from relations of the size of machined area, recommended finishing allowance and maximum depth of cut, a main machining method is selected, a number of cut is calculated, cutting tools including toolholders and inserts are selected, and values for cutting parameters are determined. A cutting tool selection procedure is proposed for toolholders and inserts of ISO code in rough cutting, and some important parameters such as holder style, tool approach angle, tool function and its direction are described in detail. In order to demonstrate the validity of the system a case study is performed.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.461-471
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• 2017

In this paper we propose a feature selection method identifying important features in the semivarying coefficient model. One important issue in semivarying coefficient model is how to estimate the parametric and nonparametric components. Another issue is how to identify important features in the varying and the constant effects. We propose a feature selection method able to address this issue using generalized cross validation functions of the varying coefficient least squares support vector regression (LS-SVR) and the linear LS-SVR. Numerical studies indicate that the proposed method is quite effective in identifying important features in the varying and the constant effects in the semivarying coefficient model.

• 대한산업공학회지
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• 제36권3호
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• pp.164-175
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• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권5호
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• pp.295-304
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• 2003

In this paper, we proposed a hardware-oriented Genetic Algorithm Processor(GAP) based on subpopulation architecture for high-performance convergence and reducing computation time. The proposed architecture was applied to enhancing population diversity for correspondence to premature convergence. In addition, the crossover operator selection and linear ranking subpop selection were newly employed for efficient exploration. As stochastic search space selection through linear ranking and suitable genetic operator selection with respect to the convergence state of each subpopulation was used, the elapsed time of searching optimal solution was shortened. In the experiments, the computation speed was increased by over $10\%$ compared to survival-based GA and Modified-tournament GA. Especially, increased by over $20\%$ in the multi-modal function. The proposed Subpop GA processor was implemented on FPGA device APEX EP20K600EBC652-3 of AGENT 2000 design kit.

• International Journal of Contents
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• 제1권2호
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.407-416
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• 2023

In order to effectively relieve the traffic pressure of the city, ensure the smooth flow of freight and promote the development of the logistics industry, the selection of appropriate port logistics location is the basis of giving full play to the port logistics function. In order to better realize the selection of port logistics, this paper adopts the entropy weight method to set up a multi-dimensional evaluation index, and constructs the evaluation model of port logistics location. Then through the actual case, from the environmental dimension and economic competition dimension to make choices and analysis. The results show that port d has the largest logistics competitiveness and the highest relative proximity among the three indicators of hinterland city economic activity, hinterland economic structure, and port operation capacity of different port logistics locations, which has absolute advantages. It is hoped that the research results can provide a reference for the multi-dimensional selection of port logistics site selections.

• 한국임상약학회지
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• 제25권4호
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• pp.286-295
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• 2015

Objective: This experiment is to study how elderly group and their various lifestyles interact with health functional foods, according to their selection behavior. Different lifestyles will be observed closely, as well as how different health conditions and consumer involvements will affect critical decision making in selecting health functional foods. Method: Theories and discoveries from original advanced research were compared parallel to the new study. Results: First, cluster analysis and exploratory analysis were performed amongst different elder lifestyles. Lifestyle exploratory analysis was used for healthy, unique, leisure, and economical-style elders. Cluster analysis was used for material trend oriented, health oriented, complacent oriented-style elders. Health Functional Foods' selection trait Exploratory Factor Analysis showed that product's originality (function, uniqueness, specialty, compatibility, distributor, expiration date), quality (amount, daily dose, visual representation, accessibility, portability, natural ingredients), and popularity (product container, brand image, taste and smell, advertised product, domestic or import, well-known function) were the three main causes. Secondly, the amount of benefits for the elderly group health lifestyle were affected by 'Interest in health', 'Notability of the health functional food', and 'Functionality approved mark'. Specifically, the importance of, 'Interest in health', 'Notability of health functional food', and 'Functionality approved mark' were noticeably high within health oriented elders. Lastly, after examining the data from elder lifestyle's relationship with health functional food selection trait, all three different results showed equal importance. If you closely examine material trend oriented elderly group, selection trait showed distinctively high regards in 'Fundamental Attribute', 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elders showed their distinctively high regards in 'Natural Attribute', and less consideration in 'Typical Attribute' and 'Cognitive Attribute'. Complacent oriented-style elderly group showed less focus on 'Fundamental Attribute', and even less in 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elderly group concluded with above data from the fact that they showed most importance and involvement in health beneficial products that are scientifically proven. Material trend oriented elderly group showed balanced traits in their concluded data, showing that they prefer function, safety, as well as the brand image and their reputation. Also, they consider the products' outer elements, such as design and product name, in order to sense inner functions. Conclusion: So, Silver Business corporations must develop products to fulfill the market demands, and strategize marketing plans to better target the correct audience.

• 전자공학회논문지CI
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• 제41권2호
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• pp.87-94
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• 2004

특징 집합 선택은 학습 알고리즘의 전처리 과정으로 사용되기도 한다. 수집된 자료가 문제와 관련이 없다거나 중복된 정보를 갖고 있는 경우, 이를 학습 모델생성 이전에 제거함으로써 학습의 성능을 향상시킬 수 있다. 또한 탐색 공간을 감소시킬 수 있으며 저장 공간도 줄일 수 있다. 본 논문에서는 특징 집합의 추출과 추출된 특징 집합의 성능 평가를 위하여 엔트로피를 기반으로 한 휴리스틱 함수를 사용하는 새로운 특징 선택 알고리즘을 제안하였다. 탐색 방법으로는 ACS 알고리즘을 이용하였다. 그 결과 학습에 사용될 특징의 차원을 감소시킴으로써 학습 모델의 크기와 불필요한 계산 시간을 감소시킬 수 있었다.

• 한국도서관정보학회지
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• 제37권2호
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• pp.47-72
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• 2006

권장도서목록은 ‘좋은 책’을 안내하여 책의 선택을 돕는 역할을 한다. 현재 다양한 기관에서 발행되는 권장도서 목록은 도서관 및 교육현장에서 어린이 및 청소년용 독서자료 선택을 위한 선정도구로 많이 활용되고 있다. 이러한 현실을 고려해서 이 연구에서는 어린이 및 청소년도서용 권장도서목록의 생산현황을 살펴보고, 이들 전장도서목록이 선정도구로 적합한지를 평가하였다. 이후 권장도서목록이 선정도구로 기능하기 위해서, 어떻게 개발되는 것이 좋은지 그 개발방안을 제안하였다.