• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2012.05a
• /
• pp.586-591
• /
• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Journal of the Korea Society for Simulation
• /
• v.32 no.3
• /
• pp.67-74
• /
• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.9
• /
• pp.2913-2919
• /
• 2000

It is essential to get large prime numbers in the design of asymmetric encryption algorithm. However, the pseudoprime numbers with high possibility to be primes have been generally used in the asymmetric encryption algorithms, because it is very difficult to find large deterministic prime numbers. In this paper, we propose a new method of deterministic prime number generation. The prime numbers generated by the proposed method have a 100% precise prime characteristic. They are also guaranteed reliability, security strength, and an ability of primitive element generation.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2009.04a
• /
• pp.392-395
• /
• 2009

응답면 기법을 활용하여 댐구조물과 같은 사회간접자본 시설물의 파괴확률을 구할 수 있다. 본 위험성 평가과정에서 응답면기법으로 구성한 한계상태 방정식을 유전자알고리즘의 적합도 방정식으로 사용하면, 핵심타입이나 지반종류, 지반다짐정도 등의 입력설계변수의 최적화 과정 속도를 더욱 신속화 시킬 수 있다. 제안된 응답면 기법과 유전자알고리즘의 복합해석기법은 신뢰성기반 최적화프로그램으로 기존의 유전자알고리즘의 수렴속도를 더욱 빠르게 하여주고, 특히 입력변수의 상하한계가 불확실한 경우에도 만족스러운 수렴성을 보장하여준다. 한계상태 방정식의 목표신뢰도 지수를 변화시켜면 해당하는 입력변수의 최적값을 출력하여주므로, 입력변수의 제약조건에 가격함수와 같은 가중치를 벌칙함수로 부여하면 가격최적화 프로그램으로 작용하게 되며, 시설물 운영자에게는 목표신뢰도에 대한 유지관리 기법과 정도를 의사결정 할 수 있도록 하여주는 기능을 가지게 된다. 조사된 많은 댐구조물의 파괴모드가 시간에 독립적으로 시공중 또는 시공완료 후 5년이내에 다수 발생하는바, 파괴모드를 조사하고 중요한 파괴모드인 파이핑 현상에 대해서 파괴확률을 계산하고 최적유지관리를 위한 개선된 유전자알고리즘 최적화 연산을 수행하였다. 기존 댐구조물과 같이 설계변수와 하중의 변동성을 알기가 어려운 경우에 유지관리비용 최소화를 위해서 본 제안 프로그램의 확장된 버젼은 중요한 기준을 제시하여줄 것으로 기대한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.69-74
• /
• 2021

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.7 no.1
• /
• pp.9-19
• /
• 2004

The selection of comparative standard parcels should be objective and reasonable, which is an important task in the individual land price appraisal procedure. However, the current procedure is mainly done manually by government officials. Therefore, the efficiency and objectiveness of this selection procedure is not guaranteed and questionable. In this study, we first defined the problem by analyzing the current comparative standard land parcel selection method. In addition, we devised a decision tree-based method using a machine learning algorithm that is considered to be efficient and objective compared to the current selection procedure. Finally the proposed method is then applied to the study area for evaluating the appropriateness and accuracy.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.1142-1146
• /
• 2008

토양수분은 지표수의 유출과정을 설명하는 과정에서 중요인자이며, 생태수문학의 핵심변수이자 기상모형의 결정적인 입력변수이다. 또한 토양수분의 공간적 시간적 특징들은 강우 및 지하수와 토양수분간의 순환 구조를 규명하는데 매우 중요하다. 본 연구에서는 산지사면의 토양수분을 체계적으로 측정하는데 필요한 시스템의 구축을 위한 기초조사 및 사전분석에 대한 연구를 수행하였다. 우수한 토양 수분 측정 장비인 TDR 장비 매설에 앞서 대상유역 선정에 대한 여러 가지 고려사항을 검토하고 수치지형 분석 등을 통한 사전분석을 실시하였다. 대상유역을 선정하기 위해서는 대상유역의 자료획득의 용이함, 지정학적, 시스템 운영적 측면에서의 가용성, 그리고 정밀측량 및 부수적요인 등 여러 요소의 고려가 요구된다. 본 연구에서는 경기도 파주시 적성면 설마리의 설마천 유역내 감악산 범륜사 우측 산지 사면을 측정대상 사면으로, 지정학적 위치, 식생분포, 지질구조 및 심도 등의 토양특성의 고려를 통해서 선정하였다. 또한 대상 사면에 흐름 발생 및 분포를 계산하기 위해서 대상사면의 지표 및 기반암 표고를 정밀 측량하였으며, 기반암 또는 풍화대까지의 깊이를 실측하여 지표면 및 지하면의 수치지형 모형을 구축하였다. 이를 대상사면 및 지하면에 대하여 표고수치지형모형(Digital Elevation Model:DEM)으로 도식한 후 흐름 발생 공간 분포를 계산하였다. 흐름발생공간분포예측은 단방향 알고리즘, 다방향 알고리즘, 흐름 분배 알고리즘 그리고 다중무한방향 알고리즘을 사용하여 지형인자인 기여사면적과 지형습윤지수를 계산하였다. 각 분배알고리즘의 의해 도출된 지형인자들로 인한 흐름발생 공간적 분포특성을 비교하였다. 이는 합리적인 토양수분 측정시스템을 구축하는데 중요한 의사결정 수단으로 판단된다.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2000.11a
• /
• pp.415-422
• /
• 2000

퍼지라는 용어는 1962년 Zadeh가 확률이론으로 해결하기 어려운 모호한 양(Fuzzy guautity)을 다루기 위해 처음 사용하였으며, Zadeh는 1965년 처음으로 체계적인 "Fuzzy sets"이라는 논문을 발표하였다. 그 후 이론적인 발전과 더불어 여러 부분(정보이론, 시스템분석, 인공지능, 전문가시스템, 의사결정분석, 자연어 처리 등)에 걸친 응용 연구가 수행되어지고 있다.(중략)지고 있다.(중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.332-335
• /
• 2018

In recent years, artificial intelligence using big data has become a big issue in IT. Various studies are being conducted on services or technologies to effectively handle big data. The educational field, there is big data about students, but it is only a simple process to collect, lookup and store such data. In the future, it makes extensive use of artificial intelligence, machine learning, and statistical analysis to find meaningful rules, patterns, and relationships in the big data of the educational field, and to produce intelligent and useful data for the actual students. Accordingly, this study aims to design a program to predict the career of students using a decision tree algorithm based on the data from the student's classroom observations. Through a career prediction program, it is believed to be helpful to present application paths to students ' counseling and to also provide classroom behavior and direction based on the desired courses.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.3
• /
• pp.45-54
• /
• 2014

In this paper, an improved two-step P2P traffic classification scheme is proposed to overcome the limitations of the existing methods. The first step is a signature-based classifier at the packet-level. The second step consists of pattern heuristic rules and a statistics-based classifier at the flow-level. With pattern heuristic rules, the accuracy can be improved and the amount of traffic to be classified by statistics-based classifier can be reduced. Based on the analysis of different decision tree algorithms, the statistics-based classifier is implemented with REPTree. In addition, the ensemble algorithm is used to improve the performance of statistics-based classifier Through the verification with the real datasets, it is shown that our hybrid scheme provides higher accuracy and lower overhead compared to other existing schemes.