• Title/Summary/Keyword: k-fuzzy ideal

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Virtual Model Control of a Posture Balancing Biped Acrobatic Robot with Fuzzy Control for Pendulum Swing Motion Generation (진자 흔들기 퍼지 제어기가 추가된 가상모델 제어 2족 곡예로봇 자세 균형 제어)

  • Lee, Byoung-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.11
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    • pp.904-911
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    • 2001
  • A broomstick swinging biped acrobatic controller is designed and simulated to show capability of the system of controllers: virtual model controller is employed for the robot\`s posture balancing control while a higher level fuzzy controller modulate the one of the virtual model controller\`s parameter for the pendulum swinging motion generation. The robot is of 7 degree-of-freedom, 8-link planar bipedal robot having two slim legs and a body. Each leg consists of a hip joint, a knee joint, an ankle joint and the body has a free joint at the top in the head at which a freely rotating broomstick is attached. We assume that the goal for the acrobat robot is to maintain a body balance in the sagittal plane while swinging up the freely up the freely rotating pendulum. We also assume that the actuators in the joints are all ideal torque generators. The proposed system of controllers satisfies the goal and the simulation results are presented.

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Fuzzy Set Based Agent System for Adaptive Tutoring (적응형 교수 학습을 위한 퍼지 집합 기반 에이젼트 시스템)

  • Choi, Sook-Young;Yang, Hyung-Jeong
    • The KIPS Transactions:PartA
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    • v.10A no.4
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    • pp.321-330
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    • 2003
  • This paper proposes an agent-based adaptive tutoring system that monitors learning process of learners' and provides learning materials dynamically according to the analyzed learning character. Furthermore, it uses fuzzy concept to evaluate learners' ability and to provide learning materials appropriate to the level of learners'. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using agent, monitoring continually the learning process of learners 'inferencing to offer proper hints in case of incorrect answer in learning assesment, composing dynamically learning materials according to the learning feature and the evaluation of assesment, our system implements effectively adaptive instruction system. Moreover, appling the fuzzy concept to the system could naturally consider and ideal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

Disaster Recovery Priority Decision for Credit Bureau Business Information System: Fuzzy-TOPSIS Approach (신용조회업무 정보시스템의 재난복구 우선순위결정: 퍼지 TOPSIS 접근방법)

  • Yang, Dong-Gu;Kim, Ki-Yoon
    • Management & Information Systems Review
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    • v.35 no.3
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    • pp.173-193
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    • 2016
  • The aim of this paper is to extend the TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) to the fuzzy environment for solving the disaster recovery priority decision problem in credit bureau business information system. In this paper, the rating of each information systems and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. Then, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all information systems. The combination between the fuzzy set and TOPSIS brings several benefits when compared with other approaches, such that the fuzzy TOPSIS require few fuzzy judgements to parameterization, which contributes to the agility of the decision process, it does not limit the number of alternatives simultaneously evaluated, and it does not cause the ranking reversal problem when a new alternative is included in the evaluation process. This paper is demonstrated with a real case study of a credit rating agency involving 9 evaluation criteria and 9 credit bureau business information systems assessed by 6 evaluators, and provide the systematic disaster recovery framework for BCP(Business Continuity Planning) to practitioner. Finally, this paper show that the procedure of the proposed fuzzy TOPSIS method is well suited as a decision-making tool for the disaster recovery priority decision problem in credit bureau business information system.

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Robust Recurrent Wavelet Interval Type-2 Fuzzy-Neural-Network Control for DSP-Based PMSM Servo Drive Systems

  • El-Sousy, Fayez F.M.
    • Journal of Power Electronics
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    • v.13 no.1
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    • pp.139-160
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    • 2013
  • In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

Acoustic Signal based Optimal Route Selection Problem: Performance Comparison of Multi-Attribute Decision Making methods

  • Borkar, Prashant;Sarode, M.V.;Malik, L. G.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.647-669
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    • 2016
  • Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

Group Decision Making for New Professor Selection Using Fuzzy TOPSIS (퍼지 TOPSIS를 이용한 신임교수선택을 위한 집단의사결정)

  • Kim, Ki-Yoon;Yang, Dong-Gu
    • Journal of Digital Convergence
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    • v.14 no.9
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    • pp.229-239
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    • 2016
  • The aim of this paper is to extend the TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) to the fuzzy environment for solving the new professor selection problem in a university. In order to achieve the goal, the rating of each candidate and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. In this paper, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all candidates. This research derived; 1) 4 evaluation criteria(research results, education and research competency, personality, major suitability) for new professor selection, 2) the 5 step procedure of the proposed fuzzy TOPSIS method for the group decision, 3) priorities of 4 candidates in the new professor selection case. The results of this paper will be useful to practical expert who is interested in analyzing fuzzy data and its multi-criteria decision-making tool for personal selection problem in personal management. Finally, the theoretical and practical implications of the findings were discussed and the directions for future research were suggested.

A study on Generalized Synchronization in the State-Controlled Cellular Neural Network(SC-CNN)

  • Rae Youngchul;Kim Yi-gon;Tinduka Mathias
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.4
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    • pp.291-296
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    • 2005
  • In this paper, we introduce a generalized synchronization method and secure communication in the State-Controlled Cellular Neural Network (SC-CNN). We make a SC-CNN using the n-double scroll. A SC-CNN is created by applying identical n-double scroll or non-identical n-double scroll and Chua's oscillator with weak coupled method to each cell. SC-CNN synchronization was achieved using GS(Generalized Synchronization) method between the transmitter and receiver about each state variable in the SC-CNN. In order to secure communication, we have synthesizing the desired information with a SC-CNN circuit by adding the information signal to the hyper-chaos signal using the SC-CNN in the transmitter. And then, transmitting the synthesized signal to the ideal channel, we confirm secure communication by separating the information signal and the SC-CNN signal in the receiver.

An Analysis of Driver Perception of Nighttime Visibility Using Fuzzy Set Theory (퍼지집합이론을 이용한 야간 도로 시인성 평가)

  • LEE, Dong Min;Youn, Chun Joo;KIM, Young Beom
    • International Journal of Highway Engineering
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    • v.17 no.5
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    • pp.57-66
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    • 2015
  • PURPOSES: Nighttime driving is very different from daytime driving because drivers must obtain nighttime sight-distances based on road lights and headlights. Unfortunately, nighttime driving conditions in Korea are far from ideal due to poor lighting and an insufficient number of road lights and inadequate operation and maintenance of delineators. This study is conducted to develop new standards for nighttime road visibility based on experiments of driver perception for nighttime visibility conditions. METHODS : In the study, perception level and satisfaction of nighttime visibility were investigated. A total of 60 drivers participated, including 34 older drivers and 31 young drivers. To evaluate driver perceptions of nighttime road visibility, fuzzy set theory was used because the conventional analysis methods for driver perception are limited in effectiveness for considering the characteristics of perception which are subjective and vague, and are generally expressed in terms of linguistic terminologies rather than numerical parameters. RESULTS : This study found that levels of nighttime visibility, as perceived by drivers, are remarkably similar to their satisfactions in different nighttime driving conditions with a log-function relationship. Older drivers evaluated unambiguously degree of nighttime visibility but evaluations by young drivers regarding it were unclear. CONCLUSIONS : A minimum value of brightness on roads was established as YUX 30, based on final analyzed results. In other words, road lights should be installed and operated to obtain more than YUX 30 brightness for the safety and comfort of nighttime driving.

An Application of Fuzzy AHP and TOPSIS Methodology for Ranking the Factors Influencing FinTech Adoption Intention: A Comparative Study of China and Korea (FinTech 채택 의도에 영향을 미치는 요소의 순위 결정을 위한 Fuzzy AHP 및 TOPSIS 방법론의 적용 : 중국과 한국의 비교 연구)

  • Mu, Hong-Lei;Lee, Young-Chan
    • Journal of Service Research and Studies
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    • v.7 no.4
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    • pp.51-68
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    • 2017
  • Financial technology (FinTech) is an emerging financial service sector include innovations in financial literacy and investment, retail banking, education, and crypto-currencies like bitcoin. One of the crucial branch of financial technology-third-party payment (TPP) is undergoing rapid growth, with online/mobile systems replacing offline financial systems. System quality and user attitudes are key perceptions driving third-party payment usage, the importance of these perceptions, however, may be different with countries as users' thinking varies from country to country. Thus, the purpose of this study is to elaborate how factors differ from China to Korea by drawing on the unified theory of acceptance and use of technology (UTAUT2). Additionally, this study also aims to propose a multi-attribute evaluation of the third-party online payment system based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to examine the relative importance of the perceptions influencing new technology adoption intention. The results showed that the price value has the most significant influence on Chinese perceptions, while the perceived credibility has the most significant effect on Korean perceptions. Sub-criteria also performs different results to Chinese and Korean third-party online payment system.