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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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International Journal of Fuzzy Logic and Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume 3, Issue 2 - Dec 2003
Volume 3, Issue 1 - Jun 2003
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A Chaos Control Method by DFC Using State Prediction
Miyazaki, Michio ; Lee, Sang-Gu ; Lee, Seong-Hoon ; Akizuki, Kageo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 1~6
DOI : 10.5391/IJFIS.2003.3.1.001
The Delayed Feedback Control method (DFC) proposed by Pyragas applies an input based on the difference between the current state of the system, which is generating chaos orbits, and the
-time delayed state, and stabilizes the chaos orbit into a target. In DFC, the information about a position in the state space is unnecessary if the period of the unstable periodic orbit to stabilize is known. There exists the fault that DFC cannot stabilize the unstable periodic orbit when a linearlized system around the periodic point has an odd number property. There is the chaos control method using the prediction of the
-time future state (PDFC) proposed by Ushio et al. as the method to compensate this fault. Then, we propose a method such as improving the fault of the DFC. Namely, we combine DFC and PDFC with parameter W, which indicates the balance of both methods, not to lose each advantage. Therefore, we stabilize the state into the
periodic orbit, and ask for the ranges of Wand gain K using Jury` method, and determine the quasi-optimum pair of (W, K) using a genetic algorithm. Finally, we apply the proposed method to a discrete-time chaotic system, and show the efficiency through some examples of numerical experiments.
A Comparative Study on the Prediction of KOSPI 200 Using Intelligent Approaches
Bae, Hyeon ; Kim, Sung-Shin ; Kim, Hae-Gyun ; Woo, Kwang-Bang ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 7~12
DOI : 10.5391/IJFIS.2003.3.1.007
In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.쀁
A continuous solution of the heat equation based on a fuzzy system
Moon, Byung-Soo ; Hwang, In-Koo ; Kwon, Kee-Choon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 13~17
DOI : 10.5391/IJFIS.2003.3.1.013
A continuous solution of the Dirichlet boundary value problem for the heat equation
using a fuzzy system is described. We first apply the Crank-Nicolson method to obtain a discrete solution at the grid points for the heat equation. Then we find a continuous function to represent approximately the discrete values at the grid points in the form of a bicubic spline function (equation omitted) that can in turn be represented exactly by a fuzzy system. We show that the computed values at non-grid points using the bicubic spline function is much smaller than the ones obtained by linear interpolations of the values at the grid points. We also show that the fuzzy rule table in the fuzzy system representation of the bicubic spline function can be viewed as a gray scale image. Hence, the fuzzy rules provide a visual representation of the functions of two variables where the contours of different levels for the function are shown in different gray scale levels
A Dynamic Channel Allocation Algorithm Based on Time Constraints in Cellular Mobile Networks
Lee, Seong-Hoon ; Lee, Sang-Gu ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 18~22
DOI : 10.5391/IJFIS.2003.3.1.018
The new realtime applications like multimedia and realtime services in a wireless network will be dramatically increased. However, many realtime services of mobile hosts in a cell cannot be continued because of insufficiency of useful channels. Conventional channel assignment approaches didn`t properly consider the problem to serve realtime applications in a cell. This paper proposes a new realtime channel assignment algorithm based on time constraint analysis of channel requests. The proposed algorithm dynamically borrows available channels from neighboring cells. It also supports a smooth handoff which continuously serves realtime applications of the mobile hosts.
A New Artificial Immune Approach to Hardware Test Based on the Principle of Antibody Diversity
Lee, Sanghyung ; Kim, Euntai ; Park, Mignon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 23~26
DOI : 10.5391/IJFIS.2003.3.1.023
This paper proposes a new artificial immune approach to hardware test. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity. Tolerance conditions in artificial immune system correspond to the antibody in biological immune system. The suggested method is applied to the on-line monitoring of a typical FSM (a decade counter) and its effectiveness is demonstrated by the computer simulation.
A Robust On-line Signature Verification System
Ryu, Sang-Yeun ; Lee, Dae-Jong ; Chun, Myung-Geun ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 27~31
DOI : 10.5391/IJFIS.2003.3.1.027
This paper proposes a robust on-line signature verification system based on a new segmentation method and fusion scheme. The proposed segmentation method resolves the problem of segment-to-segment comparison where the variation between reference signature and input signature causes the errors in the location and the number of segments. In addition, the fusion scheme is adopted, which discriminates genuineness by calculating each feature vector`s fuzzy membership degree yielded from the proposed segmentation method. Experimental results show that the proposed signature verification system has lower False Reject Rate(FRR) for genuine signature and False Accept Rate(FAR) for forgery signature.
A XML DTD Matching using Fuzzy Similarity Measure
Kim, Chang-Suk ; Son, Dong-Cheul ; Kim, Dae-Su ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 32~36
DOI : 10.5391/IJFIS.2003.3.1.032
An equivalent schema matching among several different source schemas is very important for information integration or mining on the XML based World Wide Web. Finding most similar source schema corresponding mediated schema is a major bottleneck because of the arbitrary nesting property and hierarchical structures of XML DTD schemas. It is complex and both very labor intensive and error prune job. In this paper, we present the first complex matching of XML schema, i.e. XML DTD. The proposed method captures not only schematic information but also integrity constraints information of DTD to match different structured DTD. We show the integrity constraints based hierarchical schema matching is more semantic than the schema matching only to use schematic information and stored data.
Design and Implementation of the EEIS Considering the Load of DB Server
Kim, Chang-Geun ; Park, Byeong-Jin ; Tack, Han-Ho ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 37~43
DOI : 10.5391/IJFIS.2003.3.1.037
Current Internet system of the entrance exam information to the university that is depending on searching key to solve the overloaded problem in the network and DB server or other tools to support HTML edit, haven`t satisfied user`s wants by supplying uniformed searching system. So this thesis will establish EEIS(Entrance Examination Information System) to prevent database overload phenomena when many users request a great amount of data at the same time and improve the decrease of speed and overload problem in DB server. EEIS playa role of bridge between outside client and DB server by placing VVS(Virtual View Server) between web server and DB server. By that method this system give users several usefulness in convenience and variety by supplying realtime data searching function to user. EEIS also give inner system manager more efficiency and speed in control the management system by solving those problem. This system is design and implementation to satisfy user`s desire and give them more convenience and bring up the confidence of university that adopt this system at the end.
Fuzzy Classification Rule Learning by Decision Tree Induction
Lee, Keon-Myung ; Kim, Hak-Joon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 44~51
DOI : 10.5391/IJFIS.2003.3.1.044
Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.
Fuzzy Classifier System for Edge Detection
Sim, Kwee-Bo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 52~57
DOI : 10.5391/IJFIS.2003.3.1.052
In this paper, we propose a Fuzzy Classifier System(FCS) to find a set of fuzzy rules which can carry out the edge detection. The classifier system of Holland can evaluate the usefulness of rules represented by classifiers with repeated learning. FCS makes the classifier system be able to carry out the mapping from continuous inputs to outputs. It is the FCS that applies the method of machine learning to the concept of fuzzy logic. It is that the antecedent and consequent of classifier is same as a fuzzy rule. In this paper, the FCS is the Michigan style. A single fuzzy if-then rule is coded as an individual. The average gray levels which each group of neighbor pixels has are represented into fuzzy set. Then a pixel is decided whether it is edge pixel or not using fuzzy if-then rules. Depending on the average of gray levels, a number of fuzzy rules can be activated, and each rules makes the output. These outputs are aggregated and defuzzified to take new gray value of the pixel. To evaluate this edge detection, we will compare the new gray level of a pixel with gray level obtained by the other edge detection method such as Sobel edge detection. This comparison provides a reinforcement signal for FCS which is reinforcement learning. Also the FCS employs the Genetic Algorithms to make new rules and modify rules when performance of the system needs to be improved.
Fuzzy Modeling and Control of Wheeled Mobile Robot
Kang, Jin-Shik ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 58~65
DOI : 10.5391/IJFIS.2003.3.1.058
In this paper, a new model, which is a Takagi-Sugeno fuzzy model, for mobile robot is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and the outer loop is a PI controller designed for tracking the reference input, is suggested. Because the robot dynamics is nonlinear, it requires the controller to be insensitive to the nonlinear term. To achieve this objective, the model is developed by well known T-S fuzzy model. The design algorithm of inner state-feedback loop is regional pole-placement. In this paper, regions, for which poles of the inner state feedback loop are lie in, are formulated by LMI`s. By solving these LMI`s, we can obtain the state feedback gains for T-S fuzzy system. And this paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ(linear quadratic) cost. By using these properties, it is also shown in this paper that the PI controller can be obtained by solving the LQ problem.
Intelligent Traffic Light using Fuzzy Neural Network
Park, Myeong-Bok ; You-Sik, Hong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 66~71
DOI : 10.5391/IJFIS.2003.3.1.066
In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.
Intuitionistic Fuzzy Subgroupoids
Hur, Kul ; Jang, Su-Youn ; Kang, Hee-Won ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 72~77
DOI : 10.5391/IJFIS.2003.3.1.072
In this paper, we introduce the concepts of intuitionistic fuzzy products and intuitionistic fuzzy subgroupoids. We investigate some properties of products and subgroupoids
Multiobjective PI Controller Tuning of Multivariable Boiler Control System Using Immune Algorithm
Kim, Dong-Hwa ; Park, Jin-Ill ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 78~86
DOI : 10.5391/IJFIS.2003.3.1.078
Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.
Multiple Face Segmentation and Tracking Based on Robust Hausdorff Distance Matching
Park, Chang-Woo ; Kim, Young-Ouk ; Sung, Ha-Gyeong ; Park, Mignon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 87~92
DOI : 10.5391/IJFIS.2003.3.1.087
This paper describes a system for tracking multiple faces in an input video sequence using facial convex hull based facial segmentation and robust hausdorff distance. The algorithm adapts skin color reference map in YCbCr color space and hair color reference map in RGB color space for classifying face region. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, this algorithm computes displacement of the point set between frames using a robust hausdorff distance and the best possible displacement is selected. Finally, the initial face model is updated using the displacement. We provide an example to illustrate the proposed tracking algorithm, which efficiently tracks rotating and zooming faces as well as existing multiple faces in video sequences obtained from CCD camera.
On the Design of Simple-structured Adaptive Fuzzy Logic Controllers
Park, Byung-Jae ; Kwak, Seong-Woo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 93~99
DOI : 10.5391/IJFIS.2003.3.1.093
One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC`s. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC`s) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC`s are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.
One-Class Support Vector Learning and Linear Matrix Inequalities
Park, Jooyoung ; Kim, Jinsung ; Lee, Hansung ; Park, Daihee ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 100~104
DOI : 10.5391/IJFIS.2003.3.1.100
The SVDD(support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to consider the problem of modifying the SVDD into the direction of utilizing ellipsoids instead of balls in order to enable better classification performance. After a brief review about the original SVDD method, this paper establishes a new method utilizing ellipsoids in feature space, and presents a solution in the form of SDP(semi-definite programming) which is an optimization problem based on linear matrix inequalities.
Optimal Traffic Information using Fuzzy Neural Network
Hong, You-Sik ; Lee, Choul--Ki ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 105~111
DOI : 10.5391/IJFIS.2003.3.1.105
This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen`t consider vehicle length.
Proposed Neural Network Approach for Monitoring Plant Status in Korean Next Generation Reactors
Varde, P.V. ; Hur, Seop ; Lee, D.Y. ; Moon, B.S. ; Han, J.B. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 112~120
DOI : 10.5391/IJFIS.2003.3.1.112
This paper reports the development work carried out in respect of a proposed application of Neural Network approach for the Korean Next generation Reactor (KNGR) now referred as APR-1400. The emphasis is on establishing the methodology and the approach to be adopted towards realizing this application in the next generation reactors. Keeping in view the advantages and limitation of Artificial Neural Network Approach, the role of ANN has been limited to plant status or to be more precise plant transient monitoring. The simulation work carried out so far and the results obtained shows that artificial neural network approach caters to the requirements of plant status monitoring and qualifies to be incorporated as a part of proposed operator support systems of the referenced nuclear power plant.
Wavelet-Based Fuzzy Modeling Using a DNA Coding Method
Joo, Young-Hoon ; Lee, Veun-Woo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 121~126
DOI : 10.5391/IJFIS.2003.3.1.121
In this paper, we propose a new wavelet-based fuzzy modeling using a DNA coding method. Generally, it is well known that the DNA coding method is more diverse in the knowledge expression and better in the optimization performance than the genetic algorithm (GA) because it can encode more plentiful genetic informations based on the biological DNA. The proposed method can construct a fuzzy model using the wavelet transform, in which the coefficients are identified by the DNA coding method. Thus, we can effectively get the fuzzy model of the nonlinear system by using the advantages of both wavelet transform and DNA coding method. In order to demonstrate the superiority of the proposed method, it is compared with modeling method using the conventional GA.
Wrapper Generation for Collecting Comparative Shopping Information
Shin, Ju-Ri ; Sohn, Bong-Ki ; Lee, Keon-Myung t ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 3, issue 1, 2003, Pages 127~132
DOI : 10.5391/IJFIS.2003.3.1.127
This paper proposes a wrapper generation method for collecting comparative shopping information from various Internet shopping malls. The proposed method is a kind of supervised learning method to learn wrappers from sample web pages along with information locations designated by the administrators. It generates wrappers expressed in the form of generalized tags sequences and frame filling procedures for semi-structured web pages. The paper also presents how to use the learned wrappers and describes a prototype system which implemented the proposed ideas and methods.