• Title/Summary/Keyword: Decision Diagram

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Development of Decision Support System Using Decision Analysis Cycle (의사결정분석사이클을 활용한 기업경영 의사결정지원체계 (DSS) 개발 : DACUL)

  • Choe, Su-Dong;Kim, Jae-Gyeong;Jeong, Byeong-Ho;Kim, Seong-Hui
    • IE interfaces
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    • v.2 no.1
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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.

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Risk-based Decision Model to Estimate the Contingency for Large Construction Projects (리스크 분석에 기초한 대형건설공사의 예비비 산정에 관한 연구)

  • Kim Du-Yon;Han Goo-Soo;Han Seung-Hun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.485-490
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    • 2003
  • Nowadays the rapid change in construction environment getting more globalized and complicated has caused lots of unexpected risks from inside and out of the country, so more sophisticated construction management strategies are being strongly needed. This paper suggests a risk management model with which we can estimate the appropriate contingency by quantifying the amount of probable risks immanent in large construction projects, which have a high degree of uncertainty in the anticipation of the total construction cost. To develop the model, the risk factors that make cost variations are elicited based on the real data of the contingencies assigned to the past projects. Furthermore, the influential relationship of risk factors is structured by applying the CRM(Cost Risk Model) which is the synthetic model of Monte Carlo Simulation, Influence Diagram and Decision Tree. The ultimate outcome of this research can by validated by tile case study with a large construction project performed.

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FAST BDD TRUNCATION METHOD FOR EFFICIENT TOP EVENT PROBABILITY CALCULATION

  • Jung, Woo-Sik;Han, Sang-Hoon;Yang, Joon-Eon
    • Nuclear Engineering and Technology
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    • v.40 no.7
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    • pp.571-580
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    • 2008
  • A Binary Decision Diagram (BDD) is a graph-based data structure that calculates an exact top event probability (TEP). It has been a very difficult task to develop an efficient BDD algorithm that can solve a large problem since it is highly memory consuming. In order to solve a large reliability problem within limited computational resources, many attempts have been made, such as static and dynamic variable ordering schemes, to minimize BDD size. Additional effort was the development of a ZBDD (Zero-suppressed BDD) algorithm to calculate an approximate TEP. The present method is the first successful application of a BDD truncation. The new method is an efficient method to maintain a small BDD size by a BDD truncation during a BDD calculation. The benchmark tests demonstrate the efficiency of the developed method. The TEP rapidly converges to an exact value according to a lowered truncation limit.

Anti-air Unit Learning Model Based on Multi-agent System Using Neural Network (신경망을 이용한 멀티 에이전트 기반 대공방어 단위 학습모형)

  • Choi, Myung-Jin;Lee, Sang-Heon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.11 no.5
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    • pp.49-57
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    • 2008
  • In this paper, we suggested a methodology that can be used by an agent to learn models of other agents in a multi-agent system. To construct these model, we used influence diagram as a modeling tool. We present a method for learning models of the other agents at the decision nodes, value nodes, and chance nodes in influence diagram. We concentrated on learning of the other agents at the value node by using neural network learning technique. Furthermore, we treated anti-air units in anti-air defense domain as agents in multi. agent system.

Development of Welding Information System for Power and Industrial Plant (발전 및 산업 설비 지원 용접 기술 정보 시스템 개발)

  • 박주용;홍성호
    • Journal of Welding and Joining
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    • v.17 no.3
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    • pp.44-49
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    • 1999
  • Power and industrial plant use various welding processes and many kinds of materials. Thus, it is a difficult task to get the proper welding information. In this research, a welding information system was developed to solve the difficulty. It consists of database system, knowledge base system and diagram analysis programs. Database system contains a large database and various searching method corresponding to the kind of information. A large part of welding information is managed by this database system. Knowledge based system is used for decision of proper welding process and analysis of weld defects. It has conversion program from text to knowledge, and inference mechanism. Finally, Diagram analysis programs carry out the calculation of ferrite content in the weld metal. By the calculation, a crack occurrence can be avoided. The developed system can be a useful tool for welding in the field of power and industrial plant.

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Study on an Integrated System using an ER Diagram for Chungcheong Rural Communities

  • Jang, Hyeon Seok;Park, Hyung keun
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.693-694
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    • 2015
  • While urban regeneration projects are currently under active execution in several old cities in Korea, there are few projects to improve the quality of life of rural communities. Considering the decline of the SOC system, deterioration of housing, and degeneration of economic feasibility, the purpose of this study is to provide solutions to realize an improved economic and social environment of rural communities through an integrated management system for traffic safety and water management systems. Therefore, this research used an Entity-Relationship Diagram to construct an integrated system for traffic safety and water management systems for Chungcheong rural communities. The ERD is prepared by depicting 7 relationships for 13 entities, including traffic accidents and agricultural products, and 26 attributes, including soil moisture and underflow storage. Consequently, it will be possible to set up a decision-making support system that can analyze and evaluate the regeneration index, technology, and management of the systems for Chungcheong rural communities, based on supplier and user perspectives

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Deciding the Optimal Shutdown Time Incorporating the Accident Forecasting Model (원자력 발전소 사고 예측 모형과 병합한 최적 운행중지 결정 모형)

  • Yang, Hee Joong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.4
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    • pp.171-178
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    • 2018
  • Recently, the continuing operation of nuclear power plants has become a major controversial issue in Korea. Whether to continue to operate nuclear power plants is a matter to be determined considering many factors including social and political factors as well as economic factors. But in this paper we concentrate only on the economic factors to make an optimum decision on operating nuclear power plants. Decisions should be based on forecasts of plant accident risks and large and small accident data from power plants. We outline the structure of a decision model that incorporate accident risks. We formulate to decide whether to shutdown permanently, shutdown temporarily for maintenance, or to operate one period of time and then periodically repeat the analysis and decision process with additional information about new costs and risks. The forecasting model to predict nuclear power plant accidents is incorporated for an improved decision making. First, we build a one-period decision model and extend this theory to a multi-period model. In this paper we utilize influence diagrams as well as decision trees for modeling. And bayesian statistical approach is utilized. Many of the parameter values in this model may be set fairly subjective by decision makers. Once the parameter values have been determined, the model will be able to present the optimal decision according to that value.

의사결경지원을 위한 지식표현 및 확률추론

  • Kim Seong Sik
    • The Mathematical Education
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    • v.32 no.1
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    • pp.75-90
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    • 1993
  • Decision making in uncertain situations that preferences of decision maker is important consists of a series of related decisions. Rule-based expert system can not represent such a complex decision problems. For these decision problems, this paper suggests a new methods IDPI(Influence Diagram-based Probabilistic Inference) which combines model-based knowledge representation and probabilistic inference, and implements a career counsellor for the university students using the combined methods.

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A Study on Validation of OFP for UAV using Auto Code Generation (자동 코드생성을 이용한 무인기용 OFP의 검증에 관한 연구)

  • Cho, Sang-Ook;Choi, Kee-Young
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.4
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    • pp.359-366
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    • 2009
  • MATLAB Autocode generation is a feature that converts a block diagram model in Simulink to a c program. Utilizing this function makes MATLAB/Simulink an integrated developing environment, from controller design to implementation. It can reduce development cost and time significantly. However, this automated process requires high reliability on the software, especially the original Simulink block diagram model. And thus, the verification of the codes becomes important. In this study, a UAV flight program which is generated with Simulink is validated and modified according to DO-178B. As a result of applying the procedures, the final program not only satisfied the functional requirement but is also verified with structural point of view with Decision Coverage 93%, Condition Coverage 95% and MC/DC 90%.

Organizational Memory Formulation by Inference Diagram

  • Lee, Kun-Chang;Nho, Jae-Bum
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1999.10a
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    • pp.42-46
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    • 1999
  • Knowledge management(KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization memory(or knowledge) is at the heart of KM success. How to create organizational memory has been debated among researchers. In literature, a wide variety of methods for creating organizational memory have been proposed only to prove that its applicability is limited to decision-making problems which require shallow or non-causal knowledge type. However, organizational memory with a sense of causal knowledge is highly required in solving complicated decision-making problems in which complex dynamics exist between various factors and influence each other with cause and effect relationship among them. In this respect, we propose a new approach to creating a causal-typed organizational memory (CATOM), which has a form of causal knowledge and is represented in a matrix form, by using an inference diagram. An algorithm for CATOM creation is suggested and applied to an illustrative example. Results show that our proposed KM approach can effectively equip an organization with semi-automated CATOM creation and inference process which is deemed useful in a highly competitive business environment.

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