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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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Journal DOI :
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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Dynamic Recommendation System for a Web Library by Using Cluster Analysis and Bayesian Learning
Choi, Jun-Hyeog ; Kim, Dae-Su ; Rim, Kee-Wook ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 385~392
DOI : 10.5391/JKIIS.2002.12.5.385
Collaborative filtering method for personalization can suggest new items and information which a user hasn t expected. But there are some problems. Not only the steps for calculating similarity value between each user is complex but also it doesn t reflect user s interest dynamically when a user input a query. In this paper, classifying users by their interest makes calculating similarity simple. We propose the a1gorithm for readjusting user s interest dynamically using the profile and Bayesian learning. When a user input a keyword searching for a item, his new interest is readjusted. And the user s profile that consists of used key words and the presence frequency of key words is designed and used to reflect the recent interest of users. Our methods of adjusting user s interest using the profile and Bayesian learning can improve the real satisfaction of users through the experiment with data set, collected in University s library. It recommends a user items which he would be interested in.
A Study on the Properness Constraint on Iterative Learning Controllers
Moon, Jung-Ho ; Doh, Tae-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 393~396
DOI : 10.5391/JKIIS.2002.12.5.393
This note investigates the necessity of properness constraint on iterative learning controllers from the viewpoint of the initial condition problem. It is shown that unless the iterative learning controller is proper, the teaming control input may grow unboundedly and thus not be feasible in practice, though the convergence of tracking error is theoretically guaranteed. In addition, this note analyzes the effects of initial condition misalignment in the iterative learning control system on the control input and convergence property.
The wavelet neural network using fuzzy concept for the nonlinear function learning approximation
Byun, Oh-Sung ; Moon, Sung-Ryong ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 397~404
DOI : 10.5391/JKIIS.2002.12.5.397
In this paper, it is proposed wavelet neural network using the fuzzy concept with the fuzzy and the multi-resolution analysis(MRA) of wavelet transform. Also, it wishes to improve any nonlinear function learning approximation using this system. Here, the fuzzy concept is used the bell type fuzzy membership function. And the composition of wavelet has a unit size. It is used the backpropagation algorithm for learning of wavelet neural network using the fuzzy concept. It is used the multi-resolution analysis of wavelet transform, the bell type fuzzy membership function and the backpropagation algorithm for learning. This structure is confirmed to be improved approximation performance than the conventional algorithms from one dimension and two dimensions function through simulation.
Fuzzy System Modeling Using New Hierarchical Structure
Kim, Do-Wan ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 405~410
DOI : 10.5391/JKIIS.2002.12.5.405
In this paper, fuzzy system modeling using new hierarchical structure is suggested for the complex and uncertain system. The proposed modeling technique Is to decompose the fuzzy rule base structure into the above-rule base and the sub-rule base. By applying hierarchical fuzzy rules, they can be used efficiently and logically. Also, hieratical fuzzy rules can improve the accuracy and the transparency of structure in the fuzzy system. The genetic algorithm is applied for optimization of the parameters and the structure of the fuzzy rules. To show the effectiveness of the proposed method, fuzzy modeling of the complex nonlinear system is provided.
Intrusion Detection System of Network Based on Biological Immune System
Sim, Kwee-Bo ; Yang, Jae-Won ; Lee, Dong-Wook ; Seo, Dong-Il ; Choi, Yang-Seo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 411~416
DOI : 10.5391/JKIIS.2002.12.5.411
Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.
Intelligent Ship s Steering Gear Control System Using Linguistic Instruction
Park, Gyei-Kark ; Seo, Ki-Yeol ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 417~423
DOI : 10.5391/JKIIS.2002.12.5.417
In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer s steering instruction is achieved via ableman. We embody ableman s suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer s linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman s experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.
Quantitative Image Qualify Assessment for Block-based DCT Image Coder using Human Visual Characteristics
Chung, Tae-Yun ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 424~431
DOI : 10.5391/JKIIS.2002.12.5.424
This paper proposes a new quantitative image assessment model which is essential to verify the performance of block-based DCT coding. The proposed model considers not only global distortions such as frequency sensitivity and channel masking using HVS based visual model, but also distortions including several local distortions caused by block-based coding.
Automatic Response and Conceptual Browsing of Internet FAQs Using Self-Organizing Maps
Ahn, Joon-Hyun ; Ryu, Jung-Won ; Cho, Sung-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 432~441
DOI : 10.5391/JKIIS.2002.12.5.432
Though many services offer useful information on internet, computer users are not so familiar with such services that they need an assistant system to use the services easily In the case of web sites, for example, the operators answer the users e-mail questions, but the increasing number of users makes it hard to answer the questions efficiently. In this paper, we propose an assistant system which responds to the users questions automatically and helps them browse the Hanmail Net FAQ (Frequently Asked Question) conceptually. This system uses two-level self-organizing map (SOM): the keyword clustering SOM and document classification SOM. The keyword clustering SOM reduces a variable length question to a normalized vector and the document classification SOM classifies the question into an answer class. Experiments on the 2,206 e-mail question data collected for a month from the Hanmail net show that this system is able to find the correct answers with the recognition rate of 95% and also the browsing based on the map is conceptual and efficient.
Nonlinear and Independent Component Analysis of EEG with Artifacts
Kim, Eung-Soo ; Shin, Dong-Sun ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 442~450
DOI : 10.5391/JKIIS.2002.12.5.442
In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.
Function Optimization and Event Clustering by Adaptive Differential Evolution
Hwang, Hee-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 451~461
DOI : 10.5391/JKIIS.2002.12.5.451
Differential evolution(DE) has been preyed to be an efficient method for optimizing real-valued multi-modal objective functions. DE's main assets are its conceptual simplicity and ease of use. However, the convergence properties are deeply dependent on the control parameters of DE. This paper proposes an adaptive differential evolution(ADE) method which combines with a variant of DE and an adaptive mechanism of the control parameters. ADE contributes to the robustness and the easy use of the DE without deteriorating the convergence. 12 optimization problems is considered to test ADE. As an application of ADE the paper presents a supervised clustering method for predicting events, what is called, an evolutionary event clustering(EEC). EEC is tested for 4 cases used widely for the validation of data modeling.
Design of Genetic Algorithm Processor(GAP) for Evolvable Hardware
Sim, Kwee-Bo ; Kim, Tae-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 462~466
DOI : 10.5391/JKIIS.2002.12.5.462
Genetic Algorithm (GA) which imitates the process of nature evolution is applied to various fields because it is simple to theory and easy to application. Recently applying GA to hardware, it is to proceed the research of Evolvable Hardware(EHW) developing the structure of hardware and reconstructing it. And it is growing a necessity of GAP that embodies the computation of GA to the hardware. Evolving by GA don't act in the software but in the hardware(GAP) will be necessary for the design of independent EHW. This paper shows the design GAP for fast reconfiguration of EHW.
A study on FCNN structure based on a α-LTSHD for an effective image processing
Byun, Oh-Sung ; Moon, Sung-Ryong ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 467~472
DOI : 10.5391/JKIIS.2002.12.5.467
In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.
A DESIGN OF QUASI TIME-OPTIMAL FUZZY CONTROL SYSTEMS
Nikolai V. Rostov ; Seog Chae ; Oh, Young-Seok ; Keum, Kyo-Un ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 473~480
DOI : 10.5391/JKIIS.2002.12.5.473
The problems of quasi time-optimal digital control are discussed. A new design methodology of quasi time-optimal fuzzy controllers based on approximation of prototype discrete controller is suggested. Four kinds of practicable structures for fuzzy controllers are considered. Examples of computer design of quasi time-optimal fuzzy control systems are given.
On-line Parameter Estimator Based on Takagi-Sugeno Fuzzy Models
Park, Chang-Woo ; Hyun, Chang-Ho ; Park, Mignon ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 481~486
DOI : 10.5391/JKIIS.2002.12.5.481
In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.
Subcategories of Fuzzy Limit Tower Spaces
Lee, Hyei-Kyung ;
Journal of Korean Institute of Intelligent Systems, volume 12, issue 5, 2002, Pages 487~490
DOI : 10.5391/JKIIS.2002.12.5.487
In this paper, we introduce the notion of fuzzy pseudotopological tower and fuzzy pretopological tower And we show that the category FPsTR of fuzzy pseudotopological tower spaces and the category FPrTR of fuzzy pretopological tower spaces are bireflective subcategoies of the category FLTR of fuzzy limit tower spaces.