• Title/Summary/Keyword: Fuzzy Rule

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An Automatic Fuzzy Rule Extraction using an Advanced Quantum Clustering and It's Application to Nonlinear Regression (개선된 Quantum 클러스터링을 이용한 자동적인 퍼지규칙 생성 및 비선형 회귀로의 응용)

  • Kim, Sung-Suk;Kwak, Keun-Chang
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.182-183
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    • 2007
  • 본 논문에서는 전형적인 비선형 회귀문제를 다루기 위해 슈뢰딩거 방정식에 의해 표현되는 Hilbert공간에서 수행되는 Quantum 클러스터링과 Mountain 함수를 이용하여, 수치적인 입출력데이터로부터 TSK 형태의 자동적인 퍼지 if-then 규칙의 생성방법을 제안한다. 여기서 슈뢰딩거 방정식은 분석적으로 확률함수로부터 유도되어질 수 있는 포텐셜 함수를 포함한다. 이 포텐셜의 최소점들은 데이터의 특성을 포함하는 클러스터 중심들과 관련되어진다. 그러나 이들 클러스터 중심들은 데이터의 수와 같으므로 퍼지 규칙을 생성하기 어려울 뿐만 아니라 수렴속도가 느린 문제점을 가지고 있다. 이러한 문제점들을 해결하기 위해서, 본 논문에서는 밀도 척도에 기초한 클러스터 중심의 근사적인 추정에 대해 간단하면서 효과적인 Mountain 함수를 이용하여 효과적인 클러스터 중심을 얻음과 동시에 적응 뉴로-퍼지 네트워크의 자동적인 퍼지 규칙을 생성하도록 한다. 자동차 MPG 예측문제에 대한 시뮬레이션 결과는 제안된 방법이 기존 문헌에서 제시한 예측성능보다 더 좋은 특성을 보임을 알 수 있었다.

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Obstacle Avoidance and Path Planning for a Mobile Robot Using Vision System and Fuzzy Rule (비전과 퍼지규칙을 이용한 이동로봇의 경로계획과 장애물회피)

  • Bae, Bong-Kyu;Lee, Won-Chang;Kang, Geun-Taek
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2769-2771
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    • 2000
  • In this paper we propose new algorithms of path planning and obstacle avoidance for an autonomous mobile robot with vision system. Distance variation is included in path planning to approach the target point and avoid obstacles well. The fuzzy rules are also applied to both trajectory planning and obstacle avoidance to improve the autonomy of mobile robot. It is shown by computer simulation that the proposed algorithm is working well.

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Overload Detection in Switching Systems using FUzzy Rrules (퍼지 규칙 생성에 의한 교환 시스템의 과부하 상태 검출)

  • 주성순;이정훈
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.6
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    • pp.79-88
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    • 1997
  • New technologies, systems, and services in telecommunication have increased the need for an efficient and robust control mechanism to protect switching systems from overload. To achieve proper control, it is necessary to find a set of parameters that can describe the system. However, it is difficult to find types of data that can form a suitable basis for control. In this paper, we categorize the load status of a switching system into three classes (i.e., normal state, pre-overload state, and overload state) and formulate the overload detection as a classification problem. We find the relationships between the load classes and a set of monitored switching system parameters by applying a fuzzy rule-generation method. The rules are automatically generated from training data. Simulation results involving a switching system is given.

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Design and Application of Gradient-descent-based Self-organizing Fuzzy Logic Controller (그래디언트 감소를 기반으로하는 자기구성 퍼지 제어기의 설계 및 응용)

  • 소상호;박동조
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.191-196
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    • 1998
  • A new Fuzzy Logic Controller(FLC) called a Gradient-Descent Based Self-Organizing Controller is presented. The Self-Organizing Controller(SOC) has two inputs such as error and change of error, and updates control rules with monitoring a performance measure. There are many works in the SOC which concentrate on the self-organizing ability in control rule base, but have a few research on the performance measure which is akin to sliding mode control. With this procedure, we can get a robust performance measure on the SOC. To verify the perfomance of proposed controller, we have performed for the cart-pole system which is one of the well-known benchmark problem in the control literature.

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Intelligent Control Based on Evolution Algorithms (진화 알고리즘을 기반으로한 지능 제어)

  • 이말례;김기태
    • Journal of Intelligence and Information Systems
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    • v.1 no.2
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    • pp.73-83
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    • 1995
  • In this paper, we propose a generating method for the optimal rules of the fuzzy rule base using evolution algorithms. With the aid of evolution algorithms optimal rules of fuzzy logic system can be automatic designed without human expert's priori experience and knowledge. can be intelligent control. The a, pp.oach presented here generating rules by self-tuning the parameters of membership functions and searchs the optimal control rules based on a fitness value which is the defined performance criterion. Computer simulations demonstrates the usefulness of the proposed method in non-linear systems.

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Indirect Adaptive Self-Regulating Fuzzy Control of Uncertain Nonlinear Systems Using Second Order Sliding Mode (2차 슬라이딩 모드를 이용한 불확실성을 갖는 비선형 시스템의 간접적응 자기조정 퍼지제어)

  • Park, Won-Sung;Yang, Hai-Won;Chung, Ki-Chull;Kim, Do-Woo
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1716-1717
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    • 2007
  • In this paper, a second order fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for a nonlinear system with unknown dynamics. The chattering effect that is a representative disadvantage of the sliding mode control is avoided by using the second order sliding mode control instead of the first order sliding mode control. The proposed sub-controller is composed of the equivalent control that is approximated by an online rule regulation sheme and the hitting control that is used to constrain the states of the sub-system to maintain on the sub-sliding surface and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

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A FUZZY-BASED APPROACH FOR TRAFFIC JAM DETECTION

  • Abd El-Tawaba, Ayman Hussein;Abd El Fattah, Tarek;Mahmood, Mahmood A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.257-263
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    • 2021
  • Though many have studied choosing one of the alternative ways to reach a destination, the factors such as average road speed, distance, and number of traffic signals, traffic congestion, safety, and services still presents an indisputable challenge. This paper proposes two approaches: Appropriate membership function and ambiguous rule-based approach. It aims to tackle the route choice problem faced by almost all drivers in any city. It indirectly helps in tackling the problem of traffic congestion. The proposed approach considers the preference of each driver which is determined in a flexible way like a human and stored in the driver profile. These preferences relate to the criteria for evaluating each candidate route, considering the average speed, distance, safety, and services available. An illustrative case study demonstrates the added value of the proposed approach compared to some other approaches.

Optimal Sub-bands Decision for Robust Watermarking (강건한 워터마킹을 위한 최적 부대역 결정)

  • Kim, Yoon-Ho;Kim, Tae-Gon
    • Journal of Advanced Navigation Technology
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    • v.11 no.1
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    • pp.105-111
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    • 2007
  • This paper is concerned with fuzzy inference-based optimal sub-bands decision scheme which is to be embedded the watermark. It concentrated not only on design of fuzzy inference algorithm but also on human visual parameters (HVP), such as contrast sensitivity, texture degree. In the first, such human visual parameters as contrast sensitivity, texture degree as well as statistical characteristics are involved to select the optimal coefficients region. Secondly, fuzzy if - then rule which can be able to adapt the wide variety of environments is developed. The performance of proposed approach is evaluated with respect to the imperceptibility and correctness of watermark. According to some experimental results, contrast sensitivity function is superior in smooth image. On the other hand, statistical characteristics provide good results in rough images.

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Power Sharing and Cost Optimization of Hybrid Renewable Energy System for Academic Research Building

  • Singh, Anand;Baredar, Prashant
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1511-1518
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    • 2017
  • Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

Sensorless Speed Control of Induction Motor using Am and FMRLC (ANN과 FMRLC를 이용한 유도전동기의 센서리스 속도제어)

  • Nam Su-Myeong;Lee Jung-Chul;Lee Hong-Gyun;Lee Young-Sil;Part Bung-Sang;Chung Dong-Hwa
    • Proceedings of the KIPE Conference
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    • 2004.07a
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    • pp.38-41
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    • 2004
  • Artificial intelligence control that use Fuzzy, Neural network, genetic algorithm etc. in the speed control of induction motor recently is studied much. Also, sensors such as Encoder and Resolver are used to receive the speed of induction motor and information of position. However, this control method or sensor use receives much effects in surroundings environment change and react sensitively to parameter change of electric motor and control Performance drops. Presume the speed and position of induction motor by ANN in this treatise, and because using FMRLC that is consisted of two Fuzzy Logic, can correct Fuzzy Rule Base through teaming and save good response special quality in change of condition such as change of parameter.

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