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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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Journal DOI :
Korean Institute of Intelligent Systems
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Volume & Issues
Volume 2, Issue 3 - Dec 2002
Volume 2, Issue 2 - Jun 2002
Volume 2, Issue 1 - Mar 2002
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A Study on Development of Visual Navigation System based on Neural Network Learning
Shin, Suk-Young ; Lee, Jang-Hee ; You, Yang-Jun ; Kang, Hoon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 1~8
DOI : 10.5391/IJFIS.2002.2.1.001
It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads without any specific marks such as painted guide line or tape. In this method the robot navigates with visual sensors, which uses visual information to navigate itself along the read. The Neural Network System was used to learn driving pattern and decide where to move. In this paper, I will present a vision-based process for AMR(Autonomous Mobile Robot) that is able to navigate on the indoor read with simple computation. We used a single USB-type web camera to construct smaller and cheaper navigation system instead of expensive CCD camera.
A Study on Improving the Effectiveness of Information Retrieval Through P-norm, RF, LCAF
Kim, Young-cheon ; Lee, Sung-joo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 9~14
DOI : 10.5391/IJFIS.2002.2.1.009
Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.
Automatic Detection of Interstitial Lung Disease using Neural Network
Kouda, Takaharu ; Kondo, Hiroshi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 15~19
DOI : 10.5391/IJFIS.2002.2.1.015
Automatic detection of interstitial lung disease using Neural Network is presented. The rounded opacities in the pneumoconiosis X-ray photo are picked up quickly by a back propagation (BP) neural network with several typical training patterns. The training patterns from 0.6 mm
to 4.0 mm
are made by simple circles. The total evaluation is done from the size and figure categorization. Mary simulation examples show that the proposed method gives much reliable result than traditional ones.
Behavior Evolution of Autonomous Mobile Robot(AMR) using Genetic Programming Based on Evolvable Hardware
Sim, Kwee-Bo ; Lee, Dong-Wook ; Zhang, Byoung-Tak ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 20~25
DOI : 10.5391/IJFIS.2002.2.1.020
This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. Genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy for evolvable hardware by combining proposed method with other`s striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.
Cluster-based Information Retrieval with Tolerance Rough Set Model
Ho, Tu-Bao ; Kawasaki, Saori ; Nguyen, Ngoc-Binh ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 26~32
DOI : 10.5391/IJFIS.2002.2.1.026
The objectives of this paper are twofold. First is to introduce a model for representing documents with semantics relatedness using rough sets but with tolerance relations instead of equivalence relations (TRSM). Second is to introduce two document hierarchical and nonhierarchical clustering algorithms based on this model and TRSM cluster-based information retrieval using these two algorithms. The experimental results show that TRSM offers an alterative approach to text clustering and information retrieval.
Development of Insulation Degradation Diagnosis System for Electrical Plant
Kim, Yi-Gon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 33~37
DOI : 10.5391/IJFIS.2002.2.1.033
Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.
Fast Iterative Solving Method of Fuzzy Relational Equation and its Application to Image Compression/Reconstruction
Nobuhara, Hajime ; Takama, Yasufumi ; Hirota, Kaoru ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 38~42
DOI : 10.5391/IJFIS.2002.2.1.038
A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.
Fuzzy-ART Basis Equalizer for Satellite Nonlinear Channel
Lee, Jung-Sik ; Hwang, Jae-Jeong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 43~48
DOI : 10.5391/IJFIS.2002.2.1.043
This paper discusses the application of fuzzy-ARTMAP neural network to compensate the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is the class of ART(adaptive resonance theory) architectures designed fur supervised loaming. It has capabilities not fecund in other neural network approaches, that includes a small number of parameters, no requirements fur the choice of initial weights, automatic increase of hidden units, and capability of adding new data without retraining previously trained data. By a match tracking process with vigilance parameter, fuzzy-ARTMAP neural network achieves a minimax teaming rule that minimizes predictive error and maximizes generalization. Thus, the system automatically leans a minimal number of recognition categories, or hidden units, to meet accuracy criteria. As a input-converting process for implementing fuzzy-ARTMAP equalizer, the sigmoid function is chosen to convert actual channel output to the proper input values of fuzzy-ARTMAP. Simulation studies are performed over satellite nonlinear channels. QPSK signals with Gaussian noise are generated at random from Volterra model. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP equalizer.
Fuzzy Logic-Based Moldability-Conforming System in Injection Molding
Kang, Seong-Nam ; Huh, Yong-Jeong ; Huh, Yong-Jeong ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 49~52
DOI : 10.5391/IJFIS.2002.2.1.049
Short shot is a molded part that is incomplete since insufficient material was injected into the mold. Remedial actions to solve short shot can be dune by injection molding experts based on their empirical knowledge. Modifying mold and part, changing resin to less viscous one, and adjusting process conditions are general remedies. Experts of injection molding might try to adjust process conditions such as mold temperature, melt temperature, injection time based on their empirical knowledge as the first remedy because adjustment of process conditions is the most economic way in time and cost. However it is difficult to find appropriate process conditions as they are highly coupled and there are so many elements to be considered. In this paper, a fuzzy logic algorithm has been proposed to find an appropriate mold temperature. With the percentage of the insufficient quantity of an injection molded part, an appropriate mold temperature can be obtained by the fuzzy logic algorithm.
Fuzzy Model Identification Using VmGA
Park, Jong-Il ; Oh, Jae-Heung ; Joo, Young-Hoon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 53~58
DOI : 10.5391/IJFIS.2002.2.1.053
In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.
GA-based Adaptive Load Balancing Method in Distributed Systems
Lee, Seong-Hoon ; Lee, Sang-Gu ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 59~64
DOI : 10.5391/IJFIS.2002.2.1.059
In the sender-initiated load balancing algorithms, the sender continues to send an unnecessary request message fur load transfer until a receiver is found while the system load is heavy. Meanwhile, in the receiver-initiated load balancing algorithms, the receiver continues to send an unnecessary request message for load acquisition until a sender is found while the system load is light. These unnecessary request messages result in inefficient communications, low CPU utilization, and low system throughput in distributed systems. To solve these problems, in this paper, we propose a genetic algorithm based approach fur improved sender-initiated and receiver-initiated load balancing. The proposed algorithm is used for new adaptive load balancing approach. Compared with the conventional sender-initiated and receiver-initiated load balancing algorithms, the proposed algorithm decreases the response time and increases the acceptance rate.
Hybrid Fuzzy Adaptive Control of LEGO Robots
Vaseak, Jan ; Miklos, Marian ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 65~69
DOI : 10.5391/IJFIS.2002.2.1.065
The main drawback of “classical”fuzzy systems is the inability to design and maintain their database. To overcome this disadvantage many types of extensions adding the adaptivity property to those systems were designed. This paper deals with one of them a new hybrid adaptation structure, called gradient-incremental adaptive fuzzy controller connecting gradient-descent methods with the so-called self-organizing fuzzy logic controller designed by Procyk and Mamdani. The aim is to incorporate the advantages of both Principles. This controller was implemented and tested on the system of LEGO robots. The results and comparison to a ‘classical’(non-adaptive) fuzzy controller designed by a human operator are also shown here.
Intelligent Test Plan Metrics on Adaptive Use Case Approach
Kim, R. Young Chul ; Lee, Jaehyub ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 70~77
DOI : 10.5391/IJFIS.2002.2.1.070
This paper describes a design driven approach to drive intelligent test plan generation based on adaptive use case (3,5). Its foundation is an object-oriented software design approach which partitions design schema into design architecture of functional components called “design component”. A use case software development methodology of adaptive use case approach developed in I.I .T is employed which preserves this unit architecture on through to the actual code structure. Based on the partition design schema produced during the design phase of this methodology, a test plan is generated which includes a set of component and scenario based test. A software metric is introduced which produces an ordering of this set to enhance productivity and both promote and capitalize on test case reusability, This paper contains an application that illustrates the proposed approach.
Robust Stability Analysis of Fuzzy Feedback Linearization Control Systems
Park, Chang-Woo ; Lee, Chang-Hoon ; Park, Mignon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 78~82
DOI : 10.5391/IJFIS.2002.2.1.078
In this paper, we have studied a numerical stability analysis method for the robust fuzzy feedback linearization regulator using Takagi-Sugeno fuzzy model. To analyze the robust stability, we assume that uncertainty is included in the model structure with known bounds. For these structured uncertainty, the robust stability of the closed system is analyzed by applying Linear Matrix Inequalities theory following a transformation of the closed loop systems into Lur`e systems.
Smooth uniform spaces
Ramadan, A.A. ; El-Dardery, M. ; Kim, Y.C. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 83~88
DOI : 10.5391/IJFIS.2002.2.1.083
We study some properties of smooth uniform spaces. We investigate the relationship between smooth topological spaces and smooth uniform spaces. In particular, we define a subspace of a smooth uniform space and a product of smooth uniform spaces.
Wavelet Analysis to Real-Time Fabric Defects Detection in Weaving processes
Kim, Sung-Shin ; Bae, Hyeon ; Jung, Jae-Ryong ; Vachtsevanos, George J. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 2, issue 1, 2002, Pages 89~93
DOI : 10.5391/IJFIS.2002.2.1.089
This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.