• Title/Summary/Keyword: Fuzzy factor

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Critical Success Factors of TQM Implementation in Vietnamese Supporting Industries

  • TRANG, Tran Van;DO, Quang Hung
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.391-401
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    • 2020
  • The objective of this study is to prioritize the Total Quality Management (TQM) factors based on fuzzy Analytical Hierarchy Process (AHP) method in Vietnamese supporting industries. Through an in-depth literature review, eight criteria were identified. These criteria were then divided into 32 sub-criteria. The fuzzy AHP is used to determine the percent weightings of eight categories of performance criteria that were identified via a review of the quality-management literature. These criteria include management commitment, role of the quality department, training and education, continuous improvement, quality policies, quality data and reporting, communication to improve quality, and customer satisfaction orientation. An empirical analysis of the criteria of each stage using the fuzzy AHP methodology and the expert opinion of quality management are used to evaluate the percent weightings of the criteria and sub-criteria that are synonymous with TQM implementation. The results showed that management commitment is the most critical factor; among sub-criteria, supports and responsibilities of top management is the most important. The study also identified the rank order of critical success factors of TQM. The findings suggest a generic hierarchy model for organizations to prioritize the critical factors and formulate strategies for implementing TQM in supporting industries, as well as other industries in Vietnam.

Preliminary Test of Adaptive Neuro-Fuzzy Inference System Controller for Spacecraft Attitude Control

  • Kim, Sung-Woo;Park, Sang-Young;Park, Chan-Deok
    • Journal of Astronomy and Space Sciences
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    • v.29 no.4
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    • pp.389-395
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    • 2012
  • The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

Estimation of non-working days due to weather condition using fuzzy numbers (퍼지값을 이용한 기후요소 작업불능일 산정에 관한 연구)

  • Kim, Joo-Heon;Choi, Hee-Bok;Shin, Yoon-Seok;Cho, Hun-Hee;Kang, Kyung-In
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2008.11a
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    • pp.349-352
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    • 2008
  • Weather condition is the uncontrolled factor to influence the project duration. Determining non-working days due to it incorrectly leads to often change the project duration and increase the total cost as well as causing the dispute among stakeholders. When making decision of non-working days, it is important to consider the expert's experience according to the characteristic of the site and local area. Therefore this paper presented the method to estimate non-working days due to wether condition by using fuzzy numbers reflecting expert's subjective experience.

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Fuzzy Logic Based Buffer Management Algorithm to Improve Performance of Internet Traffic over ATM Networks (ATM 네트워크에서 인터넷 트래픽 성능 향상을 위한 퍼지기반 버퍼 관리 알고리즘)

  • 김희수;김관웅;박준성;배성환;전병실
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.9
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    • pp.358-365
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    • 2003
  • To support Internet traffic efficiently over ATM networks, Guaranteed Frame Rate(GFR) has been proposed in the ATM Forum. GFR provides minimum rate guarantees to VCs and allows any excess bandwidth in the network to be shared among the contending VCs in a fair manner. In this paper, we proposed a new fuzzy logic based buffer management algorithm that provides MCR guarantee and fair sharing to GFR VCs. A key feature of proposed algorithm is its ability to accept or drop a new incoming packet dynamically based on buffer condition and load ratio of VCs. This is achieved by using fuzzy logic controller for the production of a drop factor. Simulation results show that proposed scheme significantly improves fairness and TCP throughput compared with previous schemes.

Learning Method of the ADALINE Using the Fuzzy System (퍼지 시스템을 이용한 ADALINE의 학습 방식)

  • 정경권;김주웅;정성부;엄기환
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.1
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    • pp.10-18
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    • 2003
  • In this paper, we proposed a learning algorithm for the ADALINE network. The proposed algorithm exploits fuzzy system for automatic tuning of the weight parameters of the ADALINE network. The inputs of the fuzzy system are error and change of error, and the output is the weight variation. We used different scaling factor for each weights. In order to verify the effectiveness of the proposed algorithm, we peformed the simulation and experimentation for the cases of the noise cancellation and the inverted pendulum control. The results show that the proposed algorithm does not need the learning rate and improves 4he performance compared to the Widrow-Hoff delta rule for ADALINE.

The Control of a flexible Robotic Finger Driven by PZT (압전소자로 구동되는 유연성 로봇 핑거의 제어)

  • 류재춘;박종국
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.568-576
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    • 1998
  • In this thesis discuss with a flexible robotic finger design and controller which is used for the micro flexible robotic finger. So, miniaturization, precision, controller for the control of grasping force and actuator were needed. And, even if we develop a new actuator and controller, in order to use on real system, we must considerate of a many side problem. In a force control of micro flexible finger for grasping an object, the fingertip's vibration was more important task of accuracy control. And, controller were adopt the PD/PI mixed type fuzzy controller. The controller were consist of two part, one is a PD type fuzzy controller for increase the rising time response, the other is a PI type fuzzy controller for decrease of steady-state error. Especially, in a PD type fuzzy controller, we used only seven rules. And, for a PI controller, we adopt a reset factor for the control of input values. so, we have overcome the exceed of controller's input range. For the estimate of ontroller's utility and usefulness, we have experiment and computer simulation of three cases. First, we consider of unit force grasping control for a task object, which is 0.03N. Second, bounding grasping force control which is add to a sinusoidal force on the unit force. At this cases the task force is (0.03+0.01 sin wt N). And consider of following of rectangular forces.

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Maximum Power Point Tracking Controller Connecting PV System to Grid

  • Ahmed G. Abo-Khalil;Lee Dong-Choon;Choi Jong-Woo;Kim Heung-Geun
    • Journal of Power Electronics
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    • v.6 no.3
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    • pp.226-234
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    • 2006
  • Photovoltaic (PV) generators have nonlinear V-I characteristics and maximum power points which vary with illumination level and temperature. Using a maximum power point tracker (MPPT) with an intermediate converter can increase the system efficiency by matching the PV systems to the load. This paper presents a maximum power point tracker based on fuzzy logic and a control scheme for a single-phase inverter connected to the utility grid. The fuzzy logic controller (FLC) provides an adaptive nature for system performance. Also the FLC provides excellent features such as fast response, good performance and the ability to change the fuzzy parameters to improve the control system. A single-phase AC-DC inverter is used to connect the PV system to the grid utility and local loads. While a control scheme is implemented to inject the PV output power to the utility grid at unity power factor and reduced harmonic level. The simulation results have shown the effectiveness of the proposed scheme.

Fuzzy Sky-hook Control of Semi-active Suspension System Using Rotary MR Damper (회전형 MR 댐퍼를 이용한 반능동 현가장치의 퍼지 스카이-훅 제어)

  • Cho, Jeong-Mok;Joh, Joong-Seon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.5
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    • pp.701-706
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    • 2007
  • Recently, a number of researches about linear magnetorheological(MR) damper using valve-mode characteristics of MR fluid have sufficiently undertaken, but researches about rotary MR damper using shear-mode characteristics of MR fluid are not enough. In this paper, we performed vibration control of shear-mode MR damper for unlimited rotating actuator of mobile robot. Also fuzzy logic based vibration control for shear-mode MR damper is suggested. The parameters, like scaling factor of input/output and center of the triangular membership functions associated with the different linguistic variables, are tuned by genetic algorithm. Simulation results demonstrate the effectiveness of the fuzzy-skyhook controller for vibration control of shear-mode MR damper under impact force.

Energy Forecasting Information System of Optimal Electricity Generation using Fuzzy-based RERNN with GPC

  • Elumalaivasan Poongavanam;Padmanathan Kasinathan;Karunanithi Kandasamy;S. P. Raja
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2701-2717
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    • 2023
  • In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

Structural Analysis of Earthwork Productivity Influence Factors Using Fuzzy DEMATEL Method (Fuzzy DEMATEL 방법을 활용한 토공사 생산성 영향요인 구조분석)

  • Lee, Chanwoo;Kim, Hyeonmin;Kim, Hyungjun;Cho, Hunhee
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.6
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    • pp.751-760
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    • 2023
  • Enhancing productivity in earthwork projects is crucial, significantly affecting both time and cost efficiencies. However, existing research in this domain predominantly relies on qualitative data and methodologies, which may not suffice given its critical significance. This study employed the fuzzy DEMATEL method to conduct a structural analysis of variables affecting productivity in construction projects. The findings reveal that plan changes possess the most substantial overall influence on earthwork productivity, with a comprehensive strength rating of 4.58. Additionally, it was observed that precipitation data exerted the most pronounced positive impact, with a rating of 0.48. These insights are anticipated to aid in identifying and prioritizing areas for productivity enhancement in construction projects.