• Journal of Electrical Engineering and Technology
• /
• 제3권1호
• /
• pp.101-107
• /
• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.207-209
• /
• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• Journal of Information Processing Systems
• /
• 제16권2호
• /
• pp.301-317
• /
• 2020

An enterprise patch-management system (PMS) typically supplies a single point of failure (SPOF) of centralization structure. However, a Blockchain system offers features of decentralization, transaction integrity, user certification, and a smart chaincode. This study proposes a Hyperledger Fabric Blockchain-based distributed patch-management system and verifies its technological feasibility through prototyping, so that all participating users can be protected from various threats. In particular, by adopting a private chain for patch file set management, it is designed as a Blockchain system that can enhance security, log management, latest status supervision and monitoring functions. In addition, it uses a Hyperledger Fabric that owns a practical Byzantine fault tolerant consensus algorithm, and implements the functions of upload patch file set, download patch file set, and audit patch file history, which are major features of PMS, as a smart contract (chaincode), and verified this operation. The distributed ledger structure of Blockchain-based PMS can be a solution for distributor and client authentication and forgery problems, SPOF problem, and distribution record reliability problem. It not only presents an alternative to dealing with central management server loads and failures, but it also provides a higher level of security and availability.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권2호
• /
• pp.167-172
• /
• 2012

In biology the advent of the high-throughput technology for sequencing, probing, or screening has produced huge volume of data which could not be manually handled. Biologists have resorted to software tools in order to effectively handle them. This paper introduces a bioinformatics tool to help biologists find potentially interesting pathway maps from a transcriptome data set in which the expression levels of genes are described for both case and control samples. The tool accepts a transcriptome data set, and then selects and categorizes some of genes into four classes using a fuzzy filtering technique where classes are defined by membership functions. It collects and edits the pathway maps related to those selected genes without analyst' intervention. It invokes a sequence of web service functions from KEGG, which an online pathway database system, in order to retrieve related information, locate pathway maps, and manipulate them. It maintains all retrieved pathway maps in a local database and presents them to the analysts with graphical user interface. The tool has been successfully used in identifying target genes for further analysis in transcriptome study of human cytomegalovirous. The tool is very helpful in that it can considerably save analysts' time and efforts by collecting and presenting the pathway maps that contain some interesting genes, once a transcriptome data set is just given.

• 한국측량학회지
• /
• 제31권6_2호
• /
• pp.521-527
• /
• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• 한국경영과학회지
• /
• 제27권4호
• /
• pp.87-109
• /
• 2002

A satisfiability problem in propositional logic is the problem of checking for the existence of a set of truth values of atomic prepositions that renders an input propositional formula true. This paper describes an empirical investigation of a particular integer programming approach, using the set covering model, to solve satisfiability problems. Our satisfiability engine, SETSAT, is a fully integrated, linear programming based, branch and bound method using various symbolic routines for the reduction of the logic formulas. SETSAT has been implemented in the integer programming shell MINTO which, in turn, uses the CPLEX linear programming system. The logic processing routines were written in C and integrated into the MINTO functions. The experiments were conducted on a benchmark set of satisfiability problems that were compiled at the University of Ulm in Germany. The computational results indicate that our approach is competitive with the state of the art.

• East Asian mathematical journal
• /
• 제12권1호
• /
• pp.85-92
• /
• 1996

• International Journal of Control, Automation, and Systems
• /
• 제4권4호
• /
• pp.438-447
• /
• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• 한국콘텐츠학회논문지
• /
• 제9권11호
• /
• pp.455-464
• /
• 2009

현재의 논문 중심적 학술정보 탐색의 한계에서 벗어나 저자 중심적 검색을 제공하기 위해서는 저자명이 갖는 동명이인의 문제가 해결되어야 한다. 그 해법으로 제시된 저자식별은 논문에 출현한 저자명 개체에 실세계 연구자에 대응하는 식별자를 부여하는 작업이다. 최근의 선도적 저자식별 연구들은 90%를 상회하는 식별 성능을 보고하고 있으나 실질적인 학술정보서비스에서 저자식별 기능이 탑재된 예는 거의 없다. 본 논문에서는 학술정보서비스에 보다 직접적으로 기여할 수 있는 광범위한 저자식별 연구를 위해 한국과학기술정보연구원에서 새롭게 구축한 대용량 저자식별 평가셋에 대해 기술한다. 평가셋은 DBLP 데이터에 출현한 고빈도 저자명들에 대해 웹 검색을 통한 수작업 식별 과정을 거쳐 만들어졌다. 현재 881개 저자명에 대해 수집된 41,673개의 저자명개체레코드로 구성되어 있으며 총 6,921명의 실세계 저자 식별자가 존재한다.

• 한국콘텐츠학회논문지
• /
• 제7권8호
• /
• pp.152-162
• /
• 2007

본 연구는 애니메이션 스튜디오 비욘드 프로시니움이 제작, 발표한 단편애니메이션 에서 사용된 공간 디자인을 연구의 대상으로 하고 있다. 애니메이션을 위한 공간 디자인은 작품 속에서 연기자(캐릭터)가 연기를 통해 작품의 이야기를 전달하기 위한 장(Playground)이라는 기본적인 기능이 있고 나아가 작품의 시간적, 공간적 배경을 설명하거나 작품속의 은유나 상징체계를 시각적으로 표현해주는 장치적인 기능이 있다. 이 같은 기능을 충족시키는 디자인 결과를 얻기 위해 본론에서는 개념적 측면으로 시나리오의 은유와 상징적 의미체계를 공간 디자인에 적용하는 경우를 분석하였다. 제작적인 측면으로는 캐릭터와 소품, 카메라를 통해 잡힌 화면 구성과 이 같은 요소들의 움직임에 따른 동선을 복합적으로 고려하는 방법에 대하여 살펴보았다. 애니메이션제작을 위한 공간디자이너는 깊이 있고 복합적인 사고를 할 수 있어야 하며 이를 실질적으로 구현 할 수 있는 기술적인 소양이 필요하다.