• 산업경영시스템학회지
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• 제20권43호
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• pp.321-331
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• 1997

Measurement of attributes is often highly subjective and imprecise, yet most MADM methods lack provisions for handling imprecise data. Frequently, decision makers must establish a ranking within a finite set of alternatives with respect to multiple attributes which have varying degrees of importance. The problem is more complex if the evaluations of alternatives according to each attribute are not expressed in precise numbers, but rather in fuzzy numbers. Analysis must allow for lack of precision and partial truth. The advantages of a fuzzy approach for MADM are that a decision maker can obtain efficient solutions all at once without trial and error, and that this approach provides better support for judging the interactive improvement of solutions in comparison with o decision making method. The algorithm used in this study is based on the concepts of vague set theory. Linguistic variables and vague values are used to facilitate a decision maker's subjective assessment about attribute weightings and the appropriateness of alternative versus selection attributes in order to obtain final scores which are called vague appropriateness indices. A numerical example is presented to show the practical applicability of this approach.

• 산업융합연구
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• 제1권2호
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• pp.125-140
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• 2003

This study examined testing condition when consumers have a strong ordinal preference and in a absence of established ordinal for a given attribute, how adding common features to two brands in a given product category affects brand choice. Research findings presented in this study are generally consistent with the preference confirmation view of choice. The data provides support for the proposition that (1) the effect of common features is moderated by the relative importance of brand attributes(Hypothesis 1) and (2) in the presence of primary attribute adding common features increases the likelihood of choosing the brand with the best value on this attribute(Hypotheses 2).

• 한국조경학회지
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• 제21권3호
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• pp.89-98
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• 1993

It is necessary for the park tree manager to have the current information about the status of trees, which can help him with right decisions. However, there are many problems in the existing management method such as huge amount of data, tedious work, and the difficult update work due to the lack of necessary data or the inappropriate data record and management method. The sole use of database management system(DBMS) cannot slove these problems because it cannot handle graphic data based on the locational information. So, it is imperative for the park manager to have locational data as well as attribute data of the park tree concerned. Therefore, the purpose of this study is to develop the personal computer-based, user friendly park tree management information system, which deals with attribute data(DBMS) and graphic data(using the CAD) together within the integrated environment. The park tree management information system developed in this study provides a complete operating environment for data input, update, query, delete, and retrieve. The major advantages of this system are as follows: 1) To search the location and distribution of trees. 2) To record, store, and manage data easily. 3) When the manager is changed, delivery of the park tree work is convenient. 4) The system can help the manager with the correct information for the efficient park tree management.

• 산경연구논집
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• 제11권1호
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• pp.7-17
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• 2020

Purpose: This study aimed at exploring the product choice tendency differences between the consciousness and unconsciousness of goal orientation when product attributes is perceived to be compatible with the goal orientation. Research design, data and methodology: Empirical study used a 2 (goal conscious vs. unconscious) × 3 (hedonic vs. performance vs. reliability attribute) between-subjects design and one control group. To verify hypotheses, χ²-test was conducted to 320 questionnaire data answered by undergraduate students of Jiangxi Normal University in China. Results: First, consumers under unconscious condition showed a higher product choice consistency based on compatibility between hedonic (performance) attribute of the product and their hedonic (performance) promotion goal-orientation than those under the conscious condition. Second, product choice effects of compatibility between reliability attribute of the product and prevention goal orientation were not significantly different between consumers' consciousness and unconsciousness of their prevention goal orientation. Conclusions: Marketers of 'under dog' should try to develop and deliver the product attributes different from the attributes of 'top dog.' And the 'top dog' marketers should help their customers to avoid the conflicts by developing the environment of inducing their goal orientation unconsciously. Brand marketers should always pay attention to the reliability attributes concerned with the prevention goal orientation.

• 한국멀티미디어학회논문지
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• 제3권5호
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• pp.550-556
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• 2000

러프집합에서는 식별불능관계와 근사공간 개념을 이용해서 불완전 정보로부터 최적화된 결정규칙을 유도하게 된다. 그러나, 처리 하고자 하는 정보에 정량적이거나 중복 또는 누락된 데이터가 포함된 경우에는 오류가 발생될 수 있으므로, 이러한 데이터들을 제거하거나 최소화시키는 방법이 필요하다. 정보처리 분야에서 불확실성이나 정보의 양을 측정하는데 사용되고 있는 엔트로피는 러프 관계 데이터베이스의 불완전 정보를 제거하는데 사용되었다. 그러나, 정보시스템에 포함될 수 있는 불완전 정보를 모두 다루지는 못하였다. 본 논문에서는 정보시스템의 조건속성과 결정속성에 포함될 수 있는 불완전 정보를 제거하기 위한 정보 이론적 척도로서 러프집합을 이용한 객체관계 엔트로피와 속성관계 엔트로피를 제시한다.

• Journal of Forest and Environmental Science
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• 제24권3호
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• pp.151-154
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• 2008

Dramatic price increases of fossil fuels and the economic development of emerging nations accelerates the transformation of forest lands into monocultures, e.g. for biofuel production. On this account, cost efficient methods to enable the monitoring of land resources has become a vital ambition. The application of remote sensing techniques has become an integral part of forest attribute estimation and mapping. The aim of this study was to evaluate the potentials of the kNN method by combining terrestrial with remotely sensed data for the development of a pixel-based monitoring system for the small scaled mosaic of different land use types of the off-reserve forests of the Goaso forest district in Ghana, West Africa. For this reason, occurrence and distribution of land use types like cocoa and non-timber forest resources, such as bamboo and raphia palms, were estimated, applying the kNN method to ASTER satellite data. Averaged overall accuracies, ranging from 79% for plantain, to 83% for oil palms, were found for single-attribute classifications, whereas a multi-attribute approach showed overall accuracies of up to 70%. Values of k between 3 and 6 seem appropriate for mapping bamboo. Optimisation of spectral bands improves results considerably.

• 한국측량학회지
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• 제18권4호
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• pp.335-342
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• 2000

본 연구는 지능형 교통시스템과의 연계성을 고려하여 도형정보와 속성정보를 구축하고 이를 통합분석하고 자 한 것이다. 도형정보는 위치확인의 편리성을 제공하기 위해 축척 1:5000의 수치지도에 지번도를 수치화하여 중첩하였다. 정확한 위치정보와 노선정보를 제공하기 위해서 시간대별 교통정보를 이용하였으며, 공간적인 위치분석을 위해 컴퍼넌트를 개발하여 분석시스템과 연결하였다. 이와 같이 구축된 데이터베이스는 질의 및 통계분석을 통해 적정노선을 효율적으로 선정할 수 있었으며, 도형정보에 지적정보를 연계하여 활용함으로써 위치정보를 보다 용이하게 제공할 수 있었다. 향후 실시간 위치정보와 교통정보가 연계된다면 실시간 지능형 교통시스템에 그 효율성이 증대될 것으로 기대된다.

• 한국건설관리학회논문집
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• 제4권1호
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• pp.106-113
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• 2003

건설 프로젝트의 자원관리는 공사원가의 절감, 건축물의 공정 및 품질확보에 직접적으로 관계되어 이외의 공사관리요소와 함께 매우 중요한 요소를 차지하고 있다. 하지만 자원소요계획은 공사초기에 수립되고 고려요소가 다양하여 전사적 차원의 자원소요계획을 수립하기에는 한계가 있고, 관리자간의 정보단절로 실적정보관리가 불가능하다. 건설공사의 유기적 관리를 위해서는 각 관리요소의 체계적 구성이 필요하며, 각 관리간의 사업수행정보와 실적자료의 주기적인 갱신으로 이루어져야 한다. 이에 현장변동상창을 반영하고 효과적인 자원소요계획을 수립하기 위해서는 비용 일정 통합관리의 실적 데이터를 이용하여 자원소요량 산출근거를 명확히 하고, 효율적인 자원소요계획체계를 구성하여야 한다. 본 논문에서는 비용$\cdot$일정 통합관리를 이용한 자원소요량 산출방법을 제시하였으며, 비용$\cdot$일정 통합관리를 이용한 자원 조달관리 업무프로세스를 분석하여 체계적인 자원소요계획 체계를 마련하였다.

• 정보관리학회지
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• 제40권4호
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• pp.279-306
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• 2023

본 연구는 다양한 관점의 이용요구가 혼재되어있는 독서자료의 속성을 파악하기 위해, 도서의 동시이용 (동시대출, 동시구매) 데이터에 기반하여 독서자료의 선택 및 이용과 관계된 서지적 속성을 분석하였다. KDC 주제, 독자대상, 이용자 연령 관련 26개 하위 속성 단위로 구분하여 서지적 속성 용어의 동시출현행렬을 생성하고 네트워크 분석을 수행한 결과, 독서자료의 서지적 속성의 세부 내용 및 두드러진 매개 역할을 파악하였다. 본 연구의 결과는 향후 도서관 OPAC을 비롯한 독서정보 시스템의 패싯 설계에 도움이 될 것이다.

• 한국국방경영분석학회지
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• 제30권1호
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• pp.1-14
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• 2004

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.