• Journal of Information Processing Systems
• /
• 제18권5호
• /
• pp.637-649
• /
• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

• 한국산학기술학회논문지
• /
• 제11권9호
• /
• pp.3196-3203
• /
• 2010

지역산업 지원사업은 지역환경의 여건과 제도적 변화와 더불어 지난 10년 동안 꾸준히 확대되어 왔다. 특히 정부주도의 산업정책에서 지역주도의 산업정책으로 패러다임이 변모하면서 지역 전략산업 및 특화산업 육성, 기술지원, 기업지원 사업 등 지역산업 육성을 위한 다양한 지원체계를 갖추게 되었다. 그동안 지역 내에서 다양하게 전개된 지역산업 지원사업의 성과와 효율성에 대한 필요성이 제기되면서 지역전략산업 육성정책을 중심으로 통합적 관점의 종합발전계획과 사업추진전략의 중요성이 부각되었다. 지역산업 지원사업의 총체적인 맥락에서 중복사업의 조정과 핵심역량을 집중적으로 관리하고 수요자 중심의 지원체계에 대한 프레임을 수립하는 것이 시급하다. 따라서 본 연구에서는 성과중심의 자율적 지역사업 포트폴리오를 구성하고 지역 전략산업의 특성 및 지원사업 유형에 따른 지역산업 육성 투자우선순위 도출을 위한 의사결정모형을 설정하여 검증하는데 그 목적이 있다. 본 연구는 충남전략산업 지원사업의 투자우선순위 의사결정을 위해 충남지역의 전략산업 및 지역산업 지원사업을 대상으로 AHP분석을 통해 전략산업과 지원사업유형별 투자우선순위를 도출하였다. 연구결과 전략산업 및 사업유형에 따른 중요도의 차이를 발견할 수 있었다. 즉, 사업유형의 우선순위가 전략산업에 따라 다르게 나타나는 것으로 볼 때 획일화된 기업지원 정책에서 벗어나 전략산업이나 기업규모에 따른 차별화된 기업지원 정책의 다양성이 요구된다는 것을 알 수 있다. 체계적인 정책수립 및 지원을 통해 기업의 경쟁력 강화 및 지역경제 활성화에 기여할 수 있도록 전략산업을 집중육성하고 차별화된 지원정책을 개발해야 할 것이다.

• 디지털산업정보학회논문지
• /
• 제6권1호
• /
• pp.197-209
• /
• 2010

Supply Chain Management have been introduced and used as strategic weapon for many companies. Large investments in the SCM was made, but many companies are not fully getting the performance from the systems. The purpose of this study is to find the determinants of SCM difussion and performance in the perspective of Innovation and Information technology Acceptance. In developing the research model, The model consists of eight independent variables(Management support, Decision Making concentration, IS strategy, training education, relative advantage, technological compatibility, task compatibility, SCM cost), two moderator variables(interorganizational and intraorganizational diffusion), three dependant variables(efficiency, effectiveness, strategic advantage).

• 인터넷정보학회논문지
• /
• 제15권6호
• /
• pp.99-106
• /
• 2014

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험 모형의 기반이 된다. 하지만 대부분의 지식 모델은 특정 지표나 정제된 데이터를 수동적으로 모델링하여 분석에 활용한다. 본 논문에서는 텍스트 마이닝 기술을 통해 방대한 비정형 정보로부터 지식 모델을 구성하는 토픽인자와 관계 노드를 생성하고 이를 통합하는 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
• /
• pp.153-158
• /
• 2006

The emergence of ubiquitous autonomic computing and network environment will change the service architecture information system which will be a new application area in SCM/logistics systems. In this study we surveyed the technical trend map of ubiquitous and its application in SCM/logistics support system design. We described the evolutional model of ubiquitous computing community for SCM/logistics system. It is consisted of three view points; self-growing, autonomic, and context-aware, which will allow the decision makers to be benefited from web and mobile technology and are useful for proactive SCM/logistics support system. Finally, we suggested a cooperative research planning for the development ubiquitous system between the government research center, university, and industry research activities.

• International Journal of Computer Science & Network Security
• /
• 제21권4호
• /
• pp.272-276
• /
• 2021

Presently, Online / Offline Users are facing cyber attacks every day. These cyber attacks affect user's performance, resources and various daily activities. Due to this critical situation, attention must be given to prevent such users through cyber attacks. The objective of this research paper is to improve the IDS systems by using machine learning approach to develop a hybrid model which controls the cyber attacks. This Hybrid model uses the available KDD 1999 intrusion detection dataset. In first step, Hybrid Model performs feature optimization by reducing the unimportant features of the dataset through decision tree, support vector machine, genetic algorithm, particle swarm optimization and principal component analysis techniques. In second step, Hybrid Model will find out the minimum number of features to point out accurate detection of cyber attacks. This hybrid model was developed by using machine learning algorithms like PSO, GA and ELM, which trained the system with available data to perform the predictions. The Hybrid Model had an accuracy of 99.94%, which states that it may be highly useful to prevent the users from cyber attacks.

• 대한원격탐사학회지
• /
• 제35권1호
• /
• pp.137-149
• /
• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• 산업경영시스템학회지
• /
• 제46권4호
• /
• pp.263-271
• /
• 2023

In the (3,3) close combat model based on the Lanchester Square Law, this study proposes a plan to optimally allocate residual combat power after the battle to other battlefields. As soon as the two camps of three units can grasp each other's information and predict the battle pattern immediately after the battle began, the Time Zero Allocation of Force (TZAF) scenario was used to initially allocate combat power to readjust the combat model. It reflects travel time, which is a "field friction" in which physical distance exists from battlefields that support combat power to battlefields that are supported. By developing existing studies that try to examine the effect of travel time on the battlefield through the combat model, this study forms a (3,3) combat model, which is a large number of minimum units. In order to achieve the combat purpose, the principle of optimal combat force operation is presented by examining the aspect that support combat power is allocated to the two battlefields and the consequent battle results. Through this, various scenarios were set in consideration of the travel time and the situation of the units, and differentiated results were obtained. Although the most traditional, it can be used as the basic logic of the training or the commander's decision-making system using the actual war game model.

• 한국CDE학회논문집
• /
• 제19권2호
• /
• pp.103-110
• /
• 2014

Engineering changes are indispensable engineering and management activities for manufactures to develop competitive products and to maintain consistency of its product data. Analysis of engineering changes provides a core functionality to support decision makings for engineering change management. This study aims to develop a method for analysis of engineering changes based on On-Line Analytical Processing (OLAP), a proven database analysis technology that has been applied to various business areas. This approach automates data processing for engineering change analysis from product databases that follow an international standard for product data management (PDM), and enables analysts to analyze various aspects of engineering changes with its OLAP operations. The study consists of modeling a standard PDM database and a multidimensional data model for engineering change analysis, implementing the standard and multidimensional models with PDM and data cube systems and applying the implemented data cube to core functions of engineering change management, the evaluation and propagation of engineering changes.

• Nuclear Engineering and Technology
• /
• 제46권6호
• /
• pp.753-772
• /
• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.