• 제목/요약/키워드: Decision Support Model

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An Efficient Decision Maki ng Method for the Selectionof a Layered Manufacturing (3차원 조형장비 선정을 위한 효율적인 의사결정 방법)

  • Byun, Hong-Seok
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.1
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    • pp.59-67
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    • 2009
  • The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

The Effects of Fit and Social Construction on Individual Performance

  • Im, Ghi-Young
    • 한국경영정보학회:학술대회논문집
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    • 2008.06a
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    • pp.29-34
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    • 2008
  • This study examines the effects of information and communication technologies on individual performance. The literature has paid a considerable amount of attention to social influence as a determinant of individual behavior. We combine task-technology fit with concepts from adaptive structuration theory to specify social influence. In our model, we suggest that individuals should receive support from proper social construction to have additional performance improvement. Empirical data from 317 individuals across 43 teams in 10 companies is used to assess the theoretical model. Our theoretical model received support from the data.

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Preliminary Study to Establish a Decision Support System in Sasang Constitutional Medicine with Clinical Data (사장체질 의사결정시스템 구축을 위한 체질 진단 자료를 이용한 예비연구)

  • Jin, Hee-Jeong;Moon, Jin-Seok;Go, Seong-Ho;Ku, Im-Hoi;Lee, Si-Woo;Lee, Do-Heon;Song, Mi-Young;Kim, Jong-Yeol
    • Korean Journal of Oriental Medicine
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    • v.13 no.2 s.20
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    • pp.75-81
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    • 2007
  • The need for the study of the revealing Sasang constitution at scientific term is increasing as the application of this discipline to the patient produces more accurate result. To obtain scientific evidence of Sasang constitution, it is crucial to analyze accumulated clinical information and associate them to the biological indices that may classify Sasang constitution. Thus, the analysis of clinical information is the most important stepping stone to go toward to the stage of developing model and decision support system (DSS) for classifying Sasang constitution. This study is a preliminary analysis of 1,109 samples collected with 171 clinical indices. To find meaningful clinical indices for classifying Sasang constitutional medicine, we applied decision tree model for them. The skin of 66.5% within whole Taeeumin is thick and non feeble. In the case of 69.8% within whole Soyangin, the skin is non feeble and slippery. In the case of 64.4% within whole Soeumin. they have feeble skin. Therefore, the property of skin can be suggested to be more important than any other index for the classification of Sasang constitution.

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Optimal Bayesian MCMC based fire brigade non-suppression probability model considering uncertainty of parameters

  • Kim, Sunghyun;Lee, Sungsu
    • Nuclear Engineering and Technology
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    • v.54 no.8
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    • pp.2941-2959
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    • 2022
  • The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

A Decision Support System for Paddy Rice Irrigation

  • Park, Seung-Woo;Chung, Ha-Woo;Kim, Byeong-Jin;Koo, Jee-Hee
    • Korean Journal of Hydrosciences
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    • v.2
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    • pp.99-113
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    • 1991
  • Integrated irrigation management system (IIMS) that is incorporated with a microcomputer-based decision support system (DSS) has been developed and applied to paddy rice irrigation systems management. The system hardwares consist of field data acquisition units, data transmission units, central data processing units, and printing and displaying units. Ridld data to be collected include incremental rainfall, streamflow and reservoir water levels, and water levels at several irrigation canal sections within an irrigation sidtricts. The softwares are to process field data, real-time forecasting, irrigation control data, and decision variables from data-base and simulation model subsystems. And the user-interface subsystems are incorporated to present the water system operators and managers the results from data and model sugsystems. User-friendly menu with animated graphic modules are adopted to help understand irrigation controls for the district. This paper issues the overal descriptions of DSS as applied to Anjuk irrigation district. The details of major model components for the irrigation controls are presented along with real-time data collection systems. The potentials of DSS have been appraised very practical and promising for better irrigation system operation and management.

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A GIS Based Spatial Decision Support System for Retail Center Locations (소매중심지 입지를 위한 GIS기반의 공간적 의사결정 지원시스템)

  • 백영기
    • Journal of the Korean Geographical Society
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    • v.36 no.3
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    • pp.278-291
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    • 2001
  • This paper is to build a spatial decision support system designed to solve problems relevant to the decision-making for retail center locations. For construction of the system this paper discusses the primary procedures of spatial modeling and issues of data, which are required for integrating spatial interaction models to GIS having capability of managing, analyzing and visualizing spatial data sets. Lexington, Kentucky, is selected as a case study to implement the spatial decision support system based on the spatial modeling module. This system for retail center locations is useful of estimating the catchment areas more accurately and analyzing resultant flow patterns. And this system can make spatial analysis efficiently for what-if scenarios such as an intended retail center or changing demand. The benefits of adopting this system allow the decision makers to plan the investment strategies and search for stable market structure.

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An Optimal Supplier Selection Model with a Sensitivity Analysis in the Online Shopping Environment (온라인 쇼핑환경에서 민감도분석을 이용한 최적공급자선정모형)

  • 장용식
    • Journal of Intelligence and Information Systems
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    • v.10 no.1
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    • pp.13-25
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    • 2004
  • In the online shopping environment, consumers suffer from the process of selecting an optimal supplier. Although comparison shopping agent-based web sites and consumers' online community sites support the selection process, they have limitations when considering diverse and dynamic purchase conditions as a whole, which is the cause of additional consumer effort for optimal supplier selection. This study provides a decision support model with a sensitivity analysis for selecting an optimal supplier considering purchase conditions as a whole. It screens suppliers with filtering factors and provides optimal suppliers through a sensitivity analysis from a Quadratic Programming model. We implemented a prototype system and showed that it could be an effective decision support system for selecting the optimal supplier in the online shopping environment.

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An Analysis of Service Robot Quality Attributes through the Kano Model and Decision Tree : Financial Service Robot for Introduction to Bank Branches (카노와 의사결정나무를 활용한 금융서비스 로봇의 품질속성 분석 : 은행지점 도입용 금융서비스 로봇 사례)

  • Song, Young-gue;Lee, Jungwoo;Han, Chang Hee
    • Journal of Information Technology Services
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    • v.20 no.2
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    • pp.111-126
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    • 2021
  • A Kano model was used to classify the quality attributes of the service robot function for actual deployment that can support and replace bank employees. Quality attributes for a total of 6 dimensions and 23 service elements were divided into bank employees and customer groups, and service priorities were derived after comparative analysis. The Decision tree model was used to supplement the excessive simplification of quality attributes by the modest number of Kano models and to classify and predict by segment market. Of the 23 services, 16 were classified into the same attributes in both groups. 6 services classified as combination attributes used a Decision tree to identify differences in perception of quality attributes among groups. In terms of basic financial services and professional financial services, it was confirmed that bank employees feel financial service robots more attractive than ordinary customers. In the design of IT convergence service, we propose a methodology for deriving quality attributes by combining a Kano model for classifying quality attributes of two groups and a Decision tree for forecasting subdivision markets.

A Decision-support System for Care Plan in Long-term Care Insurance (의사결정나무기법을 활용한 노인장기요양보험 표준급여모형 개발)

  • Han, Eun-Jeong;Lee, Jung-Suk;Kim, Dong-Geon;Kwon, Jinhee
    • The Korean Journal of Applied Statistics
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    • v.27 no.5
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    • pp.667-679
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    • 2014
  • National Health Insurance Service(NHIS) provide care-plans for beneficiaries in the long-term care insurance(LTCI) systems that help them use LTC services appropriately. The care-plan includes recommendations for the most adequate type of care (gold standard) for beneficiaries. This study develops a decision-support system to determine the appropriate type of care plan. To develop a model, we used a data set that well-trained assessors in the NHIS investigated as a gold standard for beneficiaries: nursing home care, home-visit care, home-visit bathing, home-visit nursing, or day and night care. The decision-support system was established through a decision-tree model, because it may be easy to explain the algorithm of a decision-support system to working groups and policy makers. Our results might be useful in evidence-based care planning in an LTCI system and contribute to the efficient use of LTC services.