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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 12, Issue 6 - Dec 2002
Volume 12, Issue 5 - Oct 2002
Volume 12, Issue 4 - Aug 2002
Volume 12, Issue 3 - Jun 2002
Volume 12, Issue 2 - Apr 2002
Volume 12, Issue 1 - Feb 2002
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Fuzzy Sensor Algorithm for Measuring Traffic Information using Analytic Hierarchy Process
Jin, Hyun-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 193~201
DOI : 10.5391/JKIIS.2002.12.3.193
For measuring a traffic symbolic confusion Quantity and symbolic air pleasantness, we use fuzzy sensor algorithm maded by symbolic information Quantity. Hut for implementation of fuzzy sensor, we use some symbolic information item, this method cannot produce precise output because we use vague fuzzy rule method and we cannot abundance fuzzy for precision of fuzzy rule method. For this reason, this paper introduce new fuzzy sensor algorithm composed of not fuzzy rule method but using Analytic Hierachy Process. To prove that new method is good, two type of fuzzy sensor applied to traffic signal controller and through much passing vehicle, two fuzzy sensor compared each other.
러프집합과 계층적 분류구조를 이용한 데이터마이닝에서 분류지식발견
Lee, Chul-Heui ; Seo, Seon-Hak ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 202~209
DOI : 10.5391/JKIIS.2002.12.3.202
This paper deals with simplification of classification rules for data mining and rule bases for control systems. Datamining that extracts useful information from such a large amount of data is one of important issues. There are various ways in classification methodologies for data mining such as the decision trees and neural networks, but the result should be explicit and understandable and the classification rules be short and clear. The rough sets theory is an effective technique in extracting knowledge from incomplete and inconsistent data and provides a good solution for classification and approximation by using various attributes effectively This paper investigates granularity of knowledge for reasoning of uncertain concopts by using rough set approximations and uses a hierarchical classification structure that is more effective technique for classification by applying core to upper level. The proposed classification methodology makes analysis of an information system eary and generates minimal classification rules.
An Efficient Composite Image Separation by Using Independent Component Analysis Based on Neural Networks
Cho, Yong-Hyun ; Park, Yong-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 210~218
DOI : 10.5391/JKIIS.2002.12.3.210
This paper proposes an efficient separation method of the composite images by using independent component analysis(ICA) based on neural networks of the approximate learning algorithm. The Proposed learning algorithm is the fixed point(FP) algorithm based on Secant method which can be approximately computed by only the values of function for estimating the root of objective function for optimizing entropy. The secant method is an alternative of the Newton method which is essential to differentiate the function for estimating the root. It can achieve a superior property of the FP algorithm for ICA due to simplify the composite computation of differential process. The proposed algorithm has been applied to the composite signals and image generated by random mixing matrix in the 4 signal of 500-sample and the 10 images of
, respectively The simulation results show that the proposed algorithm has better performance of the learning speed and the separation than those using the conventional algorithm based method. It also solved the training performances depending on initial points setting and the nonrealistic learning time for separating the large size image by using the conventional algorithm.
Fuzzy Clustering Algorithm for Web-mining
Lim, Young-Hee ; Song, Ji-Young ; Park, Dai-Hee ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 219~227
DOI : 10.5391/JKIIS.2002.12.3.219
The post-clustering algorithms, which cluster the result of Web search engine, have some different requirements from conventional clustering algorithms. In this paper, we propose the new post-clustering algorithm satisfying those of requirements as many as possible. The proposed fuzzy Concept ART is the form of combining the concept vector having several advantages in document clustering with fuzzy ART known as real time clustering algorithms on the basis of fuzzy set theory. Moreover we show that it can be applicable to general-purpose clustering as well as post clustering.
A Study on the Fingerprint Recognition Preprocessing using adaptive binary method
Cho, Seong-Wong ; Kim, Jae-Min ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 227~230
DOI : 10.5391/JKIIS.2002.12.3.227
An important preprocessing for fingerprint recognition is the binarization operation, which takes as an input gray-scale image and returns a binary image as the output. The difficult in performing binarization is to find an appropriate threshold value. This paper presents a new adaptive binarization method, which determines the threshold value according to the brightness of local ridges and valleys. We experimentally show that the presented method results in better performance than a traditional method.
Fuzzy Modeling and Fuzzy Rule Generation in Global Approximate Response Surfaces
Lee, Jong-Soo ; Hwang, Jeong-Su ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 231~238
DOI : 10.5391/JKIIS.2002.12.3.231
As a modeling method where the merits of fuzzy inference system and evolutionary computation are put together, evolutionary fuzzy modeling performs global approximate optimization. The paper proposes fuzzy clustering as fuzzy rule generation process which is one of the most important steps in evolutionary fuzzy modeling. With application of fuzzy clustering into the experiment or simulation results, fuzzy rules which properly describe non-linear and complex design problem can be obtained. The efficiency of evolutionary fuzzy modeling can be improved utilizing the membership degrees of data to clusters from the results of fuzzy clustering. To ensure the validity of the proposed method, the real design problem of an automotive inner trim is applied and the global approximation is achieved. Evolutionary fuzzy modeling is performed for several cases which differ in the number of clusters and the criterion of rule selection and their results are compared to prove that the proposed method can provide proper fuzzy rules for a given system and reduce computation time while maintaining the errors of modeling as a satisfactory level.
Controller Design for Delayed Nonlinear Systems with Saturating Input
Cho, Hee-Soo ; Lee, Kap-Rai ; Park, Hong-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 239~245
DOI : 10.5391/JKIIS.2002.12.3.239
In this Paper, we present a method for designing fuzzy
controllers of delayed nonlinear systems with saturating input. Takagi-Sugeno fuzzy model is employed to represent delayed nonlinear systems with saturating input. The fuzzy control systems utilize the concept of the so-called parallel distributed compensation(PDC). Using a single quadratic Lyapunov function, the globally exponential stability and
performance problem are discussed. And a sufficient condition for the existence of fuzzy
controllers is given in terms of linear matrix inequalities(LMIs). The designing fuzzy
controllers minimize an upper bound on a linear quadratic performance measure. Finally, a design example of fuzzy
controller for uncertain delayed nonlinear systems with saturating input.
Auto-Tuning of Reference Model Based PID Controller Using Immune Algorithm
Kim, Dong-Hwa ; Park, Jin-Ill ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 246~254
DOI : 10.5391/JKIIS.2002.12.3.246
In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.
Development of the Fuzzy-Based System for Stress Intensity Factor Analysis
Lee, Joon--Seong ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 255~260
DOI : 10.5391/JKIIS.2002.12.3.255
This paper describes a fuzzy-based system for analyzing the stress intensity factors (SIFs) of three-dimensional (3D) cracks. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated by the bucketing method, and ten-coded quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. The singular elements such that the mid-point nodes near crack front are shifted at the quarter-points, and these are automatically placed along the 3D crack front. The complete finite element(FE) model is generated, and a stress analysis is performed. The SIFs are calculated using the displacement extrapolation method. To demonstrate practical performances of the present system, semi-elliptical surface cracks in a inhomogeneous plate subjected to uniform tension are solved.
MEMBERSHIP FUNCTION TUNING OF FUZZY NEURAL NETWORKS BY IMMUNE ALGORITHM
Kim, Dong-Hwa ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 261~268
DOI : 10.5391/JKIIS.2002.12.3.261
This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.
Pairwise semicontinuous mapping in smooth bitopological spaces
Lee, Eun-Pyo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 269~274
DOI : 10.5391/JKIIS.2002.12.3.269
We introduce (
) fuzzy (r,s)-semiclosures and (
)-fuzzy (r,s)-semiinteriors. Using the notions, we investigate some of characteristic properties of fuzzy pairwise (r,s)-semicontinuous, fuzzy pairwise (r,s)-semiopen and fuzzy pairwise (r,s)-semiclosed mappings.
Speed Control Strategy of Soccer Robot using Genetic Algorithms
Shim, Kwee-Bo ; Kim, Jee-Youn ; Kim, Hyun-Young ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 275~281
DOI : 10.5391/JKIIS.2002.12.3.275
In this paper, in order to make a desired velocity and moving pattern of soccer robot, we Propose the speed control function with several parameters which represent the reflection ratio of distance and angle error etc. These parameter influence on the determining the speed and moving path of soccer robot. And we propose the searching method for these parameters by using genetic algorithms. As a result of finding the optimal parameter, we can move the robot more quickly in accordance with objective under variable environment.
The degrees of fuzzy net-convergences on complete MV-algebras
Lee, Eun-Pyo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 3, 2002, Pages 282~287
DOI : 10.5391/JKIIS.2002.12.3.282
In this paper, we introduce the degrees of fuzzy net-convergences in L-fuzzy topologies using complete MV-algebras. We investigate the relationships among the degrees of fuzzy convergent, fuzzy cluster and fuzzy adherent points. We study the properties of net-convergences.