• Title/Summary/Keyword: Fuzzy factor

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A Classification Method Using Data Reduction

  • Uhm, Daiho;Jun, Sung-Hae;Lee, Seung-Joo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.1-5
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    • 2012
  • Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.

A Design of the Robust Servo Controller for DC Servo-Motor Using Genetic Algorithm (유전알고리즘을 이용한 강인한 DC 서보제어기의 설계)

  • Kim, Dong-Wan;Hwang, Gi-Hyun;Hwang, Hyun-Joon;Nam, Jing-Lak;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.812-814
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    • 1999
  • In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

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Application of Neural Network Scheme to Performance Enhancement of Rheotruder

  • Kim, Sung-Ho;Lee, Young-Sam;Diaconescu, Bogdana
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.2
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    • pp.114-118
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    • 2005
  • Recently, in order to guarantee the quality of the final product from the production line, several equipments able to examine the polymer ingredients' quality are being used. Rheotruder is one of the equipments manufactured to measure the viscosity of the ingredient that is an important factor for the quality of final product. However, Rheotruder has nonlinear characteristics such as time delay which make systematic analysis difficult. In this paper, in order to enhance the performance of Rheotruder, a new scheme is introduced. It incorporates TDNN (Time Delay Neural Network) bank and Elman network to get a right decision on whether the tested ingredient is good or not. Furthermore, the proposed scheme is verified through real test execution.

Application of Neural Inverse Modeling Scheme to Optimal Parameter Tuning of Filter Test Equipment

  • Kim, Sung-Ho;Han, Yun-Jong;Bae, Geum-Dong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.172-175
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    • 2004
  • Generally, the yield rate of semiconductors is the major factor that affects directly the price of semiconductors. For a high yield rate of semiconductors, the air inside clean room is needed to be purified and high efficient filters are used for this. The filter are made of super-fine fiber and certain pinholes can be easily produced on the filter's surface by inadvertent manufacturing. As these pinholes are not easily detected with the bare sight, these pinholes exert a negative impact to filtration performance of the filter. In this research, not only the automatic test equipment for detecting pinholes is proposed, but also inverse modeling scheme based on artificial neural network is applied for tuning of its important parameters.

Fussy Measure Analysis of Public Attitude towards The Use of Manual control of Traffic (수동교통제어에 대한 여론에 관한 퍼지측도분석)

  • Jin, Hyun-Soo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.403-410
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    • 2008
  • This paper is cinderned with applying fussy measures and fuxxy integrals to analyze public attitude towards the use od manual control of traffic. To this end, a questionare on the use od manual control of traffic is set up and data are collected in expert, and layman. Factor analysis is performed to get the primary structure of public attitude. It is shown that the attitude of the responders to the questionare in each group is well explained with its hierarchical structure obtained by fuzzy measure analysis.

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System Modeling based on Genetic Algorithms for Image Restoration : Rough-Fuzzy Entropy (영상복원을 위한 유전자기반 시스템 모델링 : 러프-퍼지엔트로피)

  • 박인규;황상문;진달복
    • Science of Emotion and Sensibility
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    • v.1 no.2
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    • pp.93-103
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    • 1998
  • 효율적이고 체계적인 퍼지제어를 위해 조작자의 제어동작을 모델링하거나 공정을 모델링하는 기법이 필요하고, 또한 퍼지 추론시에 조건부의 기여도(contribution factor)의 결정과 동작부의 제어량의 결정이 추론의 결과에 중요하다. 본 논문에서는 추론시 조건부의 기여도와 동작부의 세어량이 퍼지 엔트로피의 개념하에서 수행되는 적응 퍼지 추론시스템을 제시한다. 제시된 시스템은 전방향 신경회로망의 토대위에서 구현되며 주건부의 기여도가 퍼지 엔트로피에 의하여 구해지고, 동작부의 제어량은 확장된 퍼지 엔트로피에 의하여 구해진다. 이를 위한 학습 알고리즘으로는 역전파 알고리즘을 이용하여 조건부의 파라미터의 동정을 하고 동작부 파라미터의 동정에는 국부해에 보다 강인한 유전자 알고리즘을 이용하다. 이러한 모델링 기법을 임펄스 잡음과 가우시안 잡음이 첨가된 영상에 적용하여 본 결과, 영상복원시에 발생되는 여러 가지의 경우에 대한 적응성이 보다 양호하게 유지되었고, 전체영상의 20%의 데이터만으로도 객관적 화질에 있어서 기존의 추론 방법에 비해 향상을 보였다.

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A Fuzzy Controller using normalized Scale Factor (정규화 스케일계수를 이용한 퍼지제어기)

  • 정동화;이동욱;이상윤;신위재
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.149-152
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    • 2003
  • 플랜트 모델이나 경험에 근거하여 설계된 퍼지제어기를 실제 플랜트에 적용할 경우, 모델링 오차와 플랜트에 대한 관련지식의 부족으로 만족할 만한 제어 결과를 나타내지 못할 경우가 있다. 이 경우 제어성능을 향상시키기 위해 제어기의 제어인자를 다시 조정하여야 하고, 이 조정과정은 시행착오 방법으로 수행되기 때문에 많은 시간과 비용을 필요로 한다. 본 논문에서는 정규화 된 오차와 오차 변화량를 사용하여 플랜트 응답에 따라 입력과 출력의 적절한 스케일 계수를 조정하는 퍼지제어기를 제안한다. 정규화 된 오차를 출력 소속함수의 중심과 폭에 곱해 출력 범위를 재조정하고, 플랜트 응답에 의해 입력의 스케일 계수를 결정한다. 이를 확인하기 위해 2차 플랜트에 적용하여 모의 실험을 수행하였다.

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Prediction of rock slope failure using multiple ML algorithms

  • Bowen Liu;Zhenwei Wang;Sabih Hashim Muhodir;Abed Alanazi;Shtwai Alsubai;Abdullah Alqahtani
    • Geomechanics and Engineering
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    • v.36 no.5
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    • pp.489-509
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    • 2024
  • Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R2 of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created.

A Study on the Urban Growth Patterns Focusing on Regional Characteristics (지역적 특성을 고려한 도시 성장 패턴에 관한 연구)

  • Yun, Jeong-Mi;Lee, Sung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.1
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    • pp.116-126
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    • 2006
  • The purpose of this study is to analyze the growing course of Busan, Gimhae and Jinhae and further find patterns of the urban growth. This study shows that patterns of the urban growth differ from city to city, being influenced by the city's characteristics. Acknowledging this fact would help the decision maker to determine the developing plan of the urban. The methodology for this study is as follows; Fuzzy set concept is applied to minimize the data loss. At the same time, the AHP is used to give a relative weight to each factor. In order to be able to manage the change based on the dynamic model and time, Cellular Automata is introduced to simulate the growth of urban. The results show that the pattern of Gimhae's and Jinhae's growth is the same, whereas that of Busan is different from them. That is to say, each city has regional characteristics. And the pattern of the urban growth is influenced by the regional conditions of the city.

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Evaluating Level of Quality for the Skyteam Cargo Services (스카이팀 카고의 서비스 품질에 대한 평가)

  • Na, Ji-Eun;Park, Yong-Hwa;Yun, Sin
    • Journal of Korean Society of Transportation
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    • v.29 no.6
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    • pp.75-83
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    • 2011
  • This research explores the relative importance of factors and service items that influence the air cargo service quality for provision services by the Skyteam Cargo in the Korean market. In general, the Skyteam Cargo provides a package of services which are different functions and operations of service such item as Equation Heavy (heavy and large express freight), Equation (small express freight), Variation (special freight), and Dimension (general freight). To carry out the research, the expert questionnaire survey, the Analytic Hierarchy Process (AHP) analysis had adopted to evaluate the level of quality for the provision air cargo operation services by the Skyteam Cargo at Incheon International Airport. Based on an expert survey and the AHP, five core service factors, namely, infrastructure as installed facilities, reliability, promptness, efficiency, and safety are defined.