• 제목/요약/키워드: fuzzy models

검색결과 658건 처리시간 0.025초

Integrated Software Quality Evaluation: A Fuzzy Multi-Criteria Approach

  • Challa, Jagat Sesh;Paul, Arindam;Dada, Yogesh;Nerella, Venkatesh;Srivastava, Praveen Ranjan;Singh, Ajit Pratap
    • Journal of Information Processing Systems
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    • 제7권3호
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    • pp.473-518
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    • 2011
  • Software measurement is a key factor in managing, controlling, and improving the software development processes. Software quality is one of the most important factors for assessing the global competitive position of any software company. Thus the quantification of quality parameters and integrating them into quality models is very essential. Software quality criteria are not very easily measured and quantified. Many attempts have been made to exactly quantify the software quality parameters using various models such as ISO/IEC 9126 Quality Model, Boehm's Model, McCall's model, etc. In this paper an attempt has been made to provide a tool for precisely quantifying software quality factors with the help of quality factors stated in ISO/IEC 9126 model. Due to the unpredictable nature of the software quality attributes, the fuzzy multi criteria approach has been used to evolve the quality of the software.

The Application of Fuzzy Logic to Assess the Performance of Participants and Components of Building Information Modeling

  • Wang, Bohan;Yang, Jin;Tan, Adrian;Tan, Fabian Hadipriono;Parke, Michael
    • Journal of Construction Engineering and Project Management
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    • 제8권4호
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    • pp.1-24
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    • 2018
  • In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

비 제어 상태의 레이저 직접 금속성형공정에서 적층높이의 모델링 (Modeling of Deposition Height in the Uncontrolled Laser Aided Direct Metal Deposition Process)

  • 장윤상
    • 한국기계가공학회지
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    • 제7권4호
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    • pp.128-134
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    • 2008
  • Models of the deposition heights in the uncontrolled laser aided direct metal deposition process are constructed for the enhancement of the process integrity. Linear and non-linear statistical models as well as fuzzy model are utilized as the modeling methods. The predictability of the models are evaluated with the values of the sum of square error. The algorithm to use the models in the feedback controlled system is suggested to increase the deposition height accuracy within a layer.

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T-S Fuzzy Model Based Indirect Adaptive Fuzzy Observer Design

  • Hyun Chang-Ho;Kim You-Keun;Kim Euntai;Park Mignon
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.348-353
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

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퍼지의사결정을 이용한 교량 구조물의 건전성평가 모델 (Integrity Assessment Models for Bridge Structures Using Fuzzy Decision-Making)

  • 안영기;김성칠
    • 콘크리트학회논문집
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    • 제14권6호
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    • pp.1022-1031
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    • 2002
  • 본 연구에서는 분규ㆍ회귀목-적응 뉴고 퍼지추론 시스템을 사용하여 교량 구조물에 대한 유용한 모델을 제시하였다. 퍼지결정목은 데이터집합의 입력영역이 서로 다른 영역으로 분류되고 하나의 부호나 값으로 나타내지며 데이터 정점에서 특정화시키기 위한 활동영역으로 할당되기도 한다. 분류문제로 사용되는 결정목은 가끔 퍼지결정목이라고 불려지는데, 각 최종점은 주어진 특정백터의 예측등급을 나타낸다. 회귀문제에 사용되는 결정목을 가끔 퍼지회귀목이라고 하는데, 이 때 최종점 영역은 주어진 입력백터의 예측 출력 값을 상수나 방정식으로 나타낼 수 있다. 분류ㆍ회귀목은 관련된 입력값을 선택하여 입력구역에서 분류 할 수 있는 반면에 적응 뉴로 퍼지추론 시스템은 회귀문제를 수정하고 이틀의 회귀문제를 보다 연속적이면서 간략하게 만들 수 있음을 주목해야 한다. 따라서 분류ㆍ회귀목과 적응 뉴로 퍼지추론 시스템은 서로 상보적인 것이며, 이들의 조합은 퍼지모델링을 위해 실직적인 근사식으로 구성된다.

배수펌프장의 효율적인 운영을 위한 퍼지모형의 적용 (Application of the Fuzzy Models for the Efficient Operation of Pumping Station)

  • 김윤태;심재현;정재학;안재찬
    • 한국방재학회 논문집
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    • 제4권3호
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    • pp.51-60
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    • 2004
  • 최근 도시지역의 수해요인은 내수침수불량에 기인하기 때문에 유수지 및 배수펌프장을 신설하여 유수지로 유입되는 유출량을 하천으로 강제배수하게 된다. 그러나 하수관거의 용량이 부족하여 유수지로 미처 유입되기 전에 하수관거의 역류로 침수피해가 자주 발생하고 있다. 따라서 본 연구에서는 도시 내배수 체계의 조사방법을 제시, 하수관거의 위험도를 평가하고 개선할 수 있는 방안을 제시하였다. 또한 배수펌프의 가동대수를 단순한 수위기준에서 변화시켜 실무에서 전문가가 아니더라도 사용할 수 있는 전산모형 8개를 개발하여 제시하였고, 지속기간, 설계빈도, 시간분포 등을 변화시켜 유수지 수위의 적정 조절여부를 검토하였다. 그리고 강제적인 배수에 의해 하류부의 수위영향이 예견되기 때문에 해당 유역의 수위를 안전하게 유지하면서도 하류부에 수위영향을 최소화할 수 있는 방안에 대해서도 검토하였다. 연구결과 Fuzzy 모형이 기존의 운영방법보다 더 효과적으로 유수지의 수위를 저하시킬 수 있었으며, 하류부 수위는 약 8cm 정도 감소시킬 수 있었다.

퍼지신경망을 이용한 비선형 데이터 모델링에 관한 연구 (A study on nonlinear data-based modeling using fuzzy neural networks)

  • 권오국;장욱;주영훈;최윤호;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.120-123
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    • 1997
  • This paper presents models of fuzzy inference systems that can be built from a set of input-output training data pairs through hybrid structure-parameter learning. Fuzzy inference systems has the difficulty of parameter learning. Here we develop a coding format to determine a fuzzy neural network(FNN) model by chromosome in a genetic algorithm(GA) and present systematic approach to identify the parameters and structure of FNN. The proposed FNN can automatically identify the fuzzy rules and tune the membership functions by modifying the connection weights of the networks using the GA and the back-propagation learning algorithm. In order to show effectiveness of it we simulate and compare with conventional methods.

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하이브리드 면진장치의 뉴로-퍼지 모형화 (Neuro-Fuzzy Modeling Approach for Hybrid Base Isolaton System)

  • 김현수;;이동근
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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    • pp.201-208
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    • 2005
  • Neuro-Fuzzy modeling approach is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system consists of friction pendulum systems (FPS) and a magnetorheological (MR) damper. Fuzzy model of the M damper is trained by ANFIS using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses or experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

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시간 지연을 가지는 비선형 마르코비안 점프 시스템의 퍼지 제어 (Stabilization for Markovian Jump Nonlinear Systems with Time-Delay via T-S Fuzzy Control)

  • 송민국;박진배;주영훈
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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    • pp.235-236
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    • 2008
  • This paper is concerned with the stabilization problem of Markovian jump nonlinear systems with time-delay via Takagi-Sugeno (T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a mode-independent fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stochstic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities (LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.

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Design of an Adaptive Fuzzy Controller and Its Application to Controlling Uncertain Chaotic Systems

  • Rark, Chang-woo;Lee, Chang-Hoon;Kim, Jung-Hwan;Kim, Seungho;Park, Mignon
    • Transactions on Control, Automation and Systems Engineering
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    • 제3권2호
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    • pp.95-105
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    • 2001
  • In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

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