• Asia pacific journal of information systems
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• 제10권3호
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• pp.105-120
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• 2000

The objective of this paper is to show how team study can be advanced with the aid of a current computer technology, that is distributed Artificial Intelligence(DAI). Studying distributed problem solving by using groups of artificial agents, DAI can provide important ideas and techniques for the study of team behaviors like team decision making. To demonstrate the usefulness of DAI models as team research tools, a DAI model called 'Team-Soar' was built and a simulation experiment done with the model was introduced, Here, Team-Soar models a naval command and control team consisting of four members whose mission was to identify the threat level of aircraft. The simulation experiment was performed to examine the relationships of team decision scheme and member incompetence with team performance. Generally, the results of the Team-Soar simulation met expectations and confirmed previous findings in the literature. For example, the results support the existence of main and interaction effects of team decision scheme and member competence on team performance. Certain results of the Team-Soar simulation provide new insights about team decision making, which can be tested against human subjects or empirical data.

• 대한산업공학회지
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• 제27권4호
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• pp.394-405
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• 2001

Since most real-world application data involve continuous-valued attributes, properly addressing the discretization process for constructing a decision tree is an important problem. A continuous-valued attribute is typically discretized during decision tree generation by partitioning its range into two intervals recursively. In this paper, by removing the restriction to the binary discretization, we present a hybrid multi-interval discretization algorithm for discretizing the range of continuous-valued attribute into multiple intervals. On the basis of experiment using semiconductor etching machine, it has been verified that our discretization algorithm constructs a more efficient incremental decision tree compared to previously proposed discretization algorithms.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권12호
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• pp.978-982
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• 2009

본 논문에서는 다수의 강화 학습 에이전트들의 학습 결과 및 Expert의 지식을 하나의 학습 알고리즘으로 융합하는 강화학습인 "potential-based" reinforcement learning(RL)기법에 불확실한 환경에서의 의사결정 알고리즘인 Case-based Decision Theory(CBDT)를 적용한 "RLs-CBDT"를 제안한다. 그리고 테트리스 실험을 통하여 기존의 RL 알고리즘에 비해 RLs-CBDT가 최적의 정책에 더 마르게 수렴하는 것을 보인다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(II)
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• pp.454-459
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• 2003

The process of determining whether, when, where and how to intervene, of deciding on optimum allocation of resources and minimizing the cost is a very complex problem: different track sections tend to behave differently under the effects of loading; decision-making processes for maintenance work are closely interrelated technically and economically; decision-making for maintenance plans is based on a large quantity of technical and economic information, extensive knowledge and above all experience. For that reason, It is considered very important to develope objective and computer-aided decision-making support system for track maintenance plan. On this paper, we reviewed ECOTRACK system and present the plan of develope decision-making support system for track maintenance appropriate to local condition.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.

• 한국CDE학회논문집
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• 제4권2호
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• pp.100-109
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• 1999

The bearing design includes the steps of selection bering type, selection bearing subtype, and determining the peripheral equipments. In this paper decision making methodologies are compared to propose a stepwise decision methodology to the bearing selection problem. An artificial neural network trained with design cases is used for selecting a bearing type in the first step. Then the subtype of the bearing is selected using the weighting method, high is a kind of multi-criteria decision making method. Finally, the types of peripheral equipments such as lubrication devices, seals and bearing housings are determined using a rule-based expert system.

• 한국경영과학회지
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• 제37권4호
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• pp.19-35
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• 2012

The Semantic Web technology, purporting to share, to reuse and to process by machines data stored in the Web environment, incessantly evolves to help human decision making; in particular, decision making based on data, or quantitative decision making. This trend drives researchers to fill the gap with strenuous efforts between the current state of the technology and the terminus of this evolution. The Semantic Web Constraint Language (SWCL) together with SWRL is one of these endeavors to achieve the goal. This paper focuses particularly on how to express the piecewise linear form in the context of SWCL. The importance of this ingredient can be fortified by the fact that any nonlinear expression can be approximated in the piecewise linear form. This paper will also provide the information of how it will work in the decision making process through an example of the Internet shopping mall problem.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 추계학술대회 논문집
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• pp.886-891
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• 2004

The process of determining whether, when, where and how to intervene, of deciding on optimum allocation of resources and minimizing the cost is a very complex problem: different track sections tend to behave differently under the effects of loading; decision-making processes for maintenance work are closely interrelated technically and economically; decision-making for maintenance plans is based on a large quantity of technical and economic information, extensive knowledge and above all experience. For that reason, It is considered very important to develope objective and computer-aided decision-making support system for track maintenance plan. On this paper, we made a survey of the state-of-art of decision-making support systems for track maintenance which were developed and used abroad and reviewed requirements of system and present the plan of develope decision-making support system for track maintenance appropriate to local condition.

• 가족자원경영과 정책
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• 제5권1호
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• pp.15-31
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• 2001

The purpose of this study is to identify participation-types of the family in the purchasing decision-making on items of commodities (TV, refrigerator, furniture, passenger car, housing, vacation, saving, husbands’clothing and children’s clothing). The other thing is to find who is major factors in each of the decision-making stages(the recognition of problem, the searching of information, the evaluation of alternatives and purchasing) among the subjects of decision-making (husband, wife, couple combination and family combination). To complete the purpose, the data were collected through questionnaire which 549 wives living in Seoul answered. From the data, frequency, percentage and correspondence analysis were executed by SPSS. The results of this study were briefly summarized as follows; Wives played an important role on all of decision-making stages for refrigerator, furniture, children’s clothing and husbands’clothing. Husbands played an important role on vacation and passenger car. And in case of saving, TV and housing, couple combination played an important role. It means that wives have a major influence on the purchasing process.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2007년도 춘계학술대회
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• pp.241-247
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• 2007

Multi-criteria decision making is deducing the relativistic importance in the criterion of decision making and each alternative which is able to make a variety of choices measures the preferred degree in the series of low-ranking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fun-diametral problem decision maker should solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we study about effective consumer preference to towels made of paper according to the three kinds of intensities of products from some domestic company, using the AHP.