• 산업경영시스템학회지
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• 제27권4호
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• pp.170-178
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• 2004

As quality becomes a primary leading factor of organizational success, various management strategies have been introduced to improve quality competitiveness. Quality competitiveness, however, is difficult to measure and numerous organizations are struggling to set realistic improvement objectives. The primary purpose of this research is to propose a systematic approach to help the practitioners develop an improvement plan for their organizational quality competitiveness. This approach employs DEA(Data Envelopment Analysis) to evaluate relative efficiency among companies which make efforts to improve their quality competitiveness. It presents an integer programming model to elicit an optimal improvement plan for meeting a target level. A decision support system is also developed for the managers to plan a sequential improvement plan based on both DEA model and the integer programming model.

• Journal of information and communication convergence engineering
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• 제21권3호
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• 지능정보연구
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• 제12권2호
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• pp.17-32
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• 2006

최근에 커뮤니티 컴퓨팅에서 그룹형성과 그룹 의사결정에 관한 이슈가 제기되고 있다. 그러나 기존의 커뮤니티 컴퓨팅 시스템에서는 그룹의 욕구를 인지함에 있어서 임시적인 방법으로 그룹을 형성하지 못하고 있다. 임시적인 방법의 그룹형성은 유비쿼터스 컴퓨팅의 의사결정지원 시스템과 서비스에서 중요한 특성 가운데 하나이다. 따라서 본 연구에서는 유목 커뮤니티 컴퓨팅에서 임시적으로 욕구를 인지하고 그룹을 형성할 수 있는 NAMA-US 에이전트 중심의 다중 에이전트 방법론을 제시하고자 한다. 이 방법론은 어떤 커뮤니티에서 상대적으로 작은 그룹의 복수의 개별 사용자의 그룹의사결정을 지원할 때 다음과 같은 세 가지 특성을 만족하고자 한다. 첫째 임시적인 그룹형성과, 둘째 상황인지 그룹 욕구인지, 그리고 셋째 실내. 외에서 동작 가능한 모바일 장비의 활용이다. RFID 기반의 프로토타입 시스템인 NAMA-US는 본 연구에서 제시하는 이런 개념을 실현시키기 위해 구축되었다.

• 한국지능시스템학회논문지
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• 제16권3호
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• pp.309-314
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• 2006

건축설계자들의 디자인 결정을 보조하고 설계자료들을 지원하기 위한 총합건축설계 지원시스템을 개발하기 위한 연구과정으로 선행연구에서 제안된 Fuzzy System을 토대로한 디자인 결정모델의 문제점들을 본 논문에서 보완하고자 한다. 특히, 공조설계자의 공조방식 결정과정에서 중요한 부분이라 할 수 있는 관련 설계요소들에 대한 특성과 영향정도를 논리적으로 결정과정에 반영 할 수 있는 방법을 제안하였다. 이를 위해서 의사결정방법의 하나인 AHP(Analystic Hierarchy Process)를 적정 디자인 값을 추론하는 과정에 적용하여 공조설계자의 공조방식 결정과정에 반영한 모델을 설정하였다

• Journal of Mechanical Science and Technology
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• 제14권4호
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• pp.380-392
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• 2000

A typical production-distribution system consist of three main echelons representing the retailer, distributors, and a factory each with an on-site warehouse. The system is sufficiently general and realistic to represent many industrial situations. However, decision functions and parameters have been selected to apply particularly to the production and distribution of consumer durables. The flows included in the model are materials, orders, and those information flows needed to support the material and order-rate decisions. In this work, a realistic production-distribution system has been used as a basic model, which consists of three sectors: retailer, distributor, and factory. That system is a nonlinear 25th-order continuous system interconnected between the echelons. Using a modern control algorithm, a typical multi-echelon production-distribution system using a dynamic controller is numerically simulated in the nominal plant and in the perturbed plant when the piecewise constant manufacturing decision is limited by a factory manufacturing upper-limit due to capital equipment, manpower, and factory lotsize.

• 산업경영시스템학회지
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• 제35권4호
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• pp.73-82
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• 2012

Currently, R&D investment of government is increased dramatically. However, the budget of the government is different depending on the size of ministry and priorities, and then it is difficult to obtain consensus on the budget. They did not establish decision support systems to evaluate and execute R&D budget. In this paper, we analyze factors affecting research funds by linear regression and decision tree analysis in order to increase investment efficiency in national research project. Moreover, we suggested strategies that budget is estimated reasonably.

• 한국지능시스템학회논문지
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• 제20권3호
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• pp.375-379
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• 2010

Support vector machine (SVM)은 튼튼한 이론적 배경을 가지고 있고 구조적 위험을 성공적으로 최소화하기 때문에 추천가 시스템과 같은 다양한 패턴 인식 분야에서 사용되고 있다. 하지만 SVM이 초평면을 결정할 때 이상점들은 margin 손실들을 가지고 있기 때문에 이들은 초평면을 결정하는데 매우 중요한 역할을 하고 있다. 그 이유로 SVM은 이상점들에게 매우 민감한 문제점을 갖는다. 강인한 SVM을 위해 우리는 이상점들의 margin 손실의 최대치를 제한하지만 이것은 non-convex 최적화 문제를 포함한다. 따라서 본 논문에서는 non-convex 최적화 문제에 적합한 유전자 알고리즘을 이용하여 강인한 SVM을 설계하는 방법을 제안한다. 제안하는 알고리즘의 우수성을 보여주기 위하여 UCI repository에서 선택된 여러 데이터베이스들을 이용한 실험을 수행하였다.

• International Journal of Advanced Culture Technology
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• 제12권3호
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• pp.140-147
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• 2024

Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.

• 산업공학
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• 제16권4호
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• pp.485-495
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• 2003

This paper reports on the application of the integration of mathematical programming model and database in a decision support system (DSS) for the planning of the multi-reservoir operating system. The DSS is based on a multi-objective, mixed-integer goal programming (MIGP) model, which can generate efficient solutions via the weighted-sums method (WSM). The major concern of this study is seamless, efficient integration between the mathematical model and the database, because there are significant differences in structure and content between the data for a mathematical model and the data for a conventional database application. In order to load the external optimization results on the database, we developed a systematic way of naming variable/constraint so that a rapid identification of variables/constraints is possible. An efficient database structure for planning of the multi-reservoir operating system is presented by taking advantage of the naming convention of the variable/constraint.

• Asia pacific journal of information systems
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• 제9권2호
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• pp.151-168
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• 1999

The objective of this study is to investigate the effects of different meeting modes and task types on the outcomes of group decision making. The hypotheses postulate the potential effects of different meeting modes on appropriation process; different meeting modes on group outcomes; and the appropriation process on group outcomes. A laboratory experiment was conducted. A GSS was developed using Lotus Notes for this experiment. The results provide partial support for the hypotheses derived from the theoretical model. The interaction effects between meeting modes and tasks are not always observed in the analyses. However, groups using a face-to-face meeting mode in negotiation task reach significantly higher levels of perceived outcome quality, of satisfaction with the outcome, and of satisfaction with the process than groups using a dispersed-synchronous meeting mode. It suggests that a face-to-face meeting mode can enhance the effectiveness of groups working on a negotiation task such as stakeholder analysis. Furthermore, the manner in which groups appropriate the technology significantly influence the group performance. The results support the validity and usefulness of the IRT and the AST as a GSS research framework.