• 산업경영시스템학회지
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• 제23권59호
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• pp.43-51
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• 2000

Many organizations are currently adjusting the statistical forecasts with qualitative factors. However, so for a few forecasting system with adjustment process have been developed. They have difficulties in managing knowledge and estimating the quantity of adjustment. In this study, the forecasting support system adopting the frame based knowledge representation and containing the decision making scheme for adjustment is proposed to overcome these difficulties. According to the experiments, the proposed system improves the forecasting performance on gasoline case.

• Journal of Mechanical Science and Technology
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• 제20권11호
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 추계학술대회 및 정기총회
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• pp.12-16
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• 1998

The purpose of this paper is to develop a knowledge-based real-time decision support system to support decision makers for efficient berth operation of Inchon Port. In these days, the efficient berth operation has been many studied. The berth operation rules differ from port to port and the problem is highly dependent on natural, geographical and operational environment of port. In Inchon Port, the ship's entrance into port and departure from port is extremely affected by the status of dock and berth because of capacity restriction. First, we analyzed the specific characteristics of Inchon Port such as dock based on the data of 1997. And then, we construct the database of experts knowledge for berth utilization. Finally, we build the real-time decision support system for the efficient berth operation of Inchon Port to make the better berth allocation in case of not only regular scheduling but also dynamic scheduling such as delay in berth operation and exchange of ship between berths. The DSS is developed with graphic user interface(GUI) concept to help the user determining user interactive updating of the port status. Then this DSS will be provide decision maker with an efficient and fast way to berth allocation, and reduce wastes of time, space, and manpower in Inchon Port operation.

• 한국지능시스템학회논문지
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• 제14권4호
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• pp.390-395
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• 2004

반도체 공정은 많은 단위 공정으로 이루어진 복잡하고 동적인 공정이다. 그 중 에칭공정은 반도체 생산에서 중요한 공정중 하나이다. 본 논문에서는 데이터 마이닝과 지식 획득을 통한 의사지원시스템으로 생산성과 수율을 높일 수 있는 시스템을 구성하고자 하였다. 제안된 방법은 퍼지 논리와 신경망으로 구성되는데, 신경망으로 에칭공정의 품질을 나타내는 품질에 대한 결과를 예측하고, 예측된 결과를 퍼지 추론 시스템으로 분류하는 과정으로 수행된다. 퍼지 논리에 사용된 규칙은 전문가의 지식에 기반 하여 도출되거나 데이터로부터 도출된다. 본 시스템을 통해 공정의 최적 조건을 찾아 효율을 높이는 것이 본 연구의 주요 목표이다.

• Asia pacific journal of information systems
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• 제2권1호
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• pp.35-56
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• 1992

This paper proposes a synergism of neural networks (NN) and knowledge-based decision support system (KBDSS) to effectively design an intelligent strategic planning system. Since conventional KBDSS becomes inoperative partially or totally when problem deviates slightly from the expected problem-domain, a new DSS concept is needed for designing an effective strategic planning system, where strategic planning environment is usually turbulent and consistently changing. In line with this idea, this paper developes a NN-based DSS, named ConDSS, incorporating the generalization property of NN into its knowledge base. The proposed ConDSS was extensively operated in an experimentally designed environment with three models: BCG matrix, Growth/Gain matrix, and GE matrix. The results proved very promising when encountered with unforeseen situations in comparisons with conventional KBDSS.

• 산업공학
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• 제11권2호
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.

• 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.

• 기본간호학회지
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• 제18권1호
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• pp.116-129
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• 2011

Purpose: The purpose of this study was to develop a computer decision making support system that enables nurses to utilize the computer in selecting the best decision for pain management for patients with dementia institutionalized in nursing homes. Methods: To formulate the protocol for the management of patients' pain, the researcher analyzed content of interviews with 30 nurses in three nursing homes and an expert group. A decision support computer program was formalized based on existing protocols. To evaluate the effectiveness and applicability of the system, analysis of data on patient pain management and nurse satisfaction with the system were done after the formalized decision support computer program was complete. Results: The decision support computer program for pain management for institutionalized patients with dementia was finalized after adjustments following the evaluation. Nurse satisfaction with the program was moderate. It also provided opportunity to reassess thinking about pain and pain management. Conclusions: The results indicate that this program provides nurses with useful knowledge for pain management in institutionalized patients with dementia and aids in decision making in nursing practice in nursing home.

• 산업공학
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• 제2권1호
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• pp.47-58
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• 1989

Many decision problems in the real world have uncertainty and complexity. In many cases, decision makers do not have decision-analytic knowledge enough to solve a given decision problem. This paper developes a Decision Support System(DSS) that can be used for structuring decision problem into decision tree based on the concept of influence diagram and analyzing the decision problem by following Decision Analysis Cycle. This study suggests a DSS system(DACUL) in order to implement Decision Analysis Cycle using Lotus1-2-3. DACUL system has been developed in IBM XT/AT compatible PC.