• 디지털융복합연구
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• 제10권10호
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• pp.97-106
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• 2012

과거에는 경영의사결정에 적절한 정보를 적시에 제공할 수 없기 때문에 불확실한 경영을 했으며 경영자는 주관적인 경험과 판단 등에 의지하였다. 정보기술의 발달과 더불어 발전한 정보시스템과 기술은 비즈니스 운영면에서 고도의 효율성과 생산성을 달성하기 위하여 관리자가 활용할 수 있는 가장 중요한 도구 중에 속한다. 이것의 효과는 비즈니스 실무와 관리행태의 변화가 동반되었을때 더욱 크게 나타난다. 본 연구에서는 기업의 전략적 의사결정에 필요한 문제를 해결하기 위하여 정보기술을 활용하여 필요한 정보를 획득하고 문제해결 방법론을 시뮬레이션 하여 객관적이고 정형화된 경영의사결정을 지원하는 시스템을 개발하기위한 기능요소 및 솔루션을 구조화하였다. 본 연구에서 제안하는 전략의사결정지원 시스템은 기업경영 지원기술에 관련된 것으로 IT기술을 활용하여 경영의사결정에서 요구되는 전략의사결정 문제에 있어서 최적의 시나리오를 선택하도록 하여 신뢰성 있는 기업경영에 도움을 줄 수 있는 시스템이다. 전략의사결정시스템은 개별사업 시뮬레이션과 전사사업 시뮬레이션, 전사사업 포트폴리오 관리 등 크게 세 가지 기능부문으로 나누어 볼 수 있다. 본 시스템은 객관적이고 정형화된 컨설팅 결과를 제공함으로써 신뢰성을 보장할 수 있고, 급변하는 경영 여건에 효율적으로 대응할 수 있는 유용한 효과를 기대할 수 있다.

• 국제학술발표논문집
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• The 10th International Conference on Construction Engineering and Project Management
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• pp.145-151
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• 2024

Road sign support systems are not usually well managed because bridges and pavement have budget and maintenance priority while the sign boards and sign supports are considered as miscellaneous items. The authors of this paper suggested the implementation of simplified machine learning algorithms for asset risk management in highway sign support systems. By harnessing historical and real-time data, machine learning models can forecast potential vulnerabilities, enabling early intervention and proactive maintenance protocols. The raw data were collected from the Connecticut Department of Transportation (CTDOT) asset management database that includes asset ages, repair history, installation and repair costs, and other administrative information. While there are many advanced and complicated structural deterioration prediction models, a simple deterioration curve is assumed, and prediction model has been developed using machine learning algorithm to determine the risk assessment and prediction. The integration of simplified machine learning in asset risk management for highway sign support systems not only enables predictive maintenance but also optimizes resource allocation. This approach ensures that decision-makers are not inundated with excessive detailed information, making it particularly practical for industry application.

• 한국콘텐츠학회논문지
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• 제11권4호
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• pp.312-320
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• 2011

이 논문에서는 일개 POC(Point Of Care) 시스템을 사용하는 의료기관을 중심으로 의약품 처방조제지원 시스템(Clinical Decision Support System, CDSS)과 조직성과와의 관계를 규명하는 것에 목적을 두고 있다. 이를 위하여 정보시스템 평가요소에 대해 정의를 내리고, CDSS의 성과 평가 모형을 제시하여 설문조사 분석을 통해 의약품 처방조제지원시스템의 도입 효과를 밝히고자 하였다. 분석결과 시스템 품질을 제외하고는 각 평가 영역들 사이에 인과성이 존재하는 것으로 분석되었으며, 통계적으로 유의하게 지지되는 것으로 분석되었다. 평가모형 검증결과 의약품처방최적화를 위한 CDSS의 시스템 품질이 사용자 만족도에 영향을 미친다는 근거를 발견할 수 없었다. 그러나 정보품질이 사용자의 만족도에 긍정적인 영향을 미치며 사용자 만족은 조직성과에 긍정적인 영향을 미치는 것으로 나타났다.

• 한국군사과학기술학회지
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• 제27권1호
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• pp.80-93
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• 2024

This study attempted to analyze the factors that influence the participation of beneficiary companies in the government's defense industry promotion support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions among various company information using the decision tree model, one of the data mining techniques. In addition, various rules were derived to determine the beneficiary companies of the government's support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of the government's industrial development. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the government support project will help create a sustainable future defense industry growth environment.

• 경영과학
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• 제34권1호
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• pp.1-13
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• 2017

The percentage of 3PL (Third-party Logistics), which uses third party businesses to outsource elements of the company's distribution and fulfillment services, is increasing steadily. To provide 3PL service to the customers, it is needed to estimate the total transportation cost and propose the unit cost to the customers. In this paper, we develop a decision support system for estimation of transportation cost of 3PL provider considering various transportation services, such as direct transportation, multi point visiting transportation, and cross docking. The system supports route planning of vehicles by using algorithms based on tabu search and dynamic programming.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.165-169
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• 2007

In order to develop VirtuAlmighty system, CPDM (construction project data management) and CPLM (construction project lifecycle management) model must be settled beforehand. Because most of information systems based on 3D-Design have its own database and business process. So, our team will develop collaboration management architecture of construction process for Decision Support based on PLM (Project Life-cycle Management). This architecture with business processes and Database can be used in process develop, process monitoring with many stakeholders of project, process change management, and so on.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.369-374
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• 2000

Despite their tilde application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today due to a static view far prefect progression. This study proposes a framework for estimation by learning based on a Linear Bayesian approach. As a project progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g. the expected project completion time as well as the probabilities of completing the project within talc due date and by a certain date. By Implementing such customized systems, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• 지능정보연구
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• 제6권2호
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• pp.91-98
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• 2000

Despite their wide application of some traditional project management techniques like the Program Evaluation and Review Technique, they lack of learning, one of important factors in many disciplines today, due to a static view for project progression. This study proposes a framework for estimation by loaming based on a Linear Bayesian approach. As a project Progresses, we sequentially observe the durations of completed activities. By reflecting this newly available information to update the distribution of remaining activity durations and thus project duration, we can implement a decision support system that updates e.g., the expected project completion time as well as the probabilities of completing the project within the due bate and by a certain date. By implementing such customized system, project manager can be aware of changing project status more effectively and better revise resource allocation plans.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.27-35
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• 2016

Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance. They are applied in various fields such as inductive inferences, classifications, or regressions. However, by its characteristics, they cannot provide appropriate explanations how the classification results are derived. Therefore, there are plenty of actively discussed researches about interpreting trained black-box classifiers. In this paper, we propose a method to make a fuzzy logic-based classifier using extracted rules from the artificial neural network and support vector machine in order to interpret internal structures. As an object of classification, an anomalous propagation echo is selected which occurs frequently in radar data and becomes the problem in a precipitation estimation process. After applying a clustering method, learning dataset is generated from clusters. Using the learning dataset, artificial neural network and support vector machine are implemented. After that, decision trees for each classifier are generated. And they are used to implement simplified fuzzy logic-based classifiers by rule extraction and input selection. Finally, we can verify and compare performances. With actual occurrence cased of the anomalous propagation echo, we can determine the inner structures of the black-box classifiers.

• 대한간호학회지
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• 제29권4호
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• pp.880-891
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• 1999

The purpose of this study was to describe nursing decision tasks, their characteristics, and problems associated with decision making. The subjects were 32 nurses who had at least one-year nursing experience and worked on medical-surgical units or intensive care units(ICU). They were asked to describe their decision making experiences in patient care situations and to identify the characteristics of each decisions. They were also asked to describe perceived problems associated with decision making in nursing. The responses on nursing decision tasks and problems were analyzed with content analysis and the decision characteristics were identified by statistical analysis of variance. It was found that there were 16 nursing decisions which are as follows : decisions related to interpreting and selecting appropriate strategies for pain management(6.6%) ; decisions related to providing emotional support (0.7%) ; decisions related to explaining the patient's condition and rationale for procedures(1.1%) ; decisions related to assisting patients to integrate the implications of illness and recovering into their lifestyles(2.9%) ; decisions related to detecting significant changes In patients and selecting appropriate intervention strategies (17.2%) ; decisions related to anticipating problems and selecting preventive measures(4.2%) ; decisions related to identifying emergency situations(0.4%) ; decisions related to effective management of patient crisis until physician assistance becomes available(2.8%) ; decisions related to starting and maintaining intravenous therapy(2.6%) ; decisions related to administering medications(8.1%) ; decisions related to combating the hazards of immobility(7.3%) : decisions related to treating wound management strategies(5.5%) ; decisions related to relieving patient discomfort(13.9) ; decisions related to selecting appropriate strategy according to the changing situation of the patient(18.2%) ; decisions related to selecting the best strategy for patient management(5.3%) ; and decisions related to coordinating, ordering, and meeting the various needs of the patient (3.1%). The nurses reported the fellowing problems in decision making : difficulties due to lack of knowledge and experience (18.6%) ; uncertainty and complexity of decision tasks(15.2%) ; lack of time to make decisions(2.9%) ; personal values which conflict with other staff(15.7%) ; lack of selection autonomy(30.0%) ; and organizational barriers(7.6%). Continuing education programs and decision support systems for frequent nursing decision tasks can be established on the basis of these results. Then decision ability in nurses will increase through the education programs and decision support systems, and then quality of nursing service will be better.