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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 13, Issue 6 - Dec 2003
Volume 13, Issue 5 - Oct 2003
Volume 13, Issue 4 - Aug 2003
Volume 13, Issue 3 - Jun 2003
Volume 13, Issue 2 - Apr 2003
Volume 13, Issue 1 - Feb 2003
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Function Approximation for accelerating learning speed in Reinforcement Learning
Lee, Young-Ah ; Chung, Tae-Choong ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 635~642
DOI : 10.5391/JKIIS.2003.13.6.635
Reinforcement learning got successful results in a lot of applications such as control and scheduling. Various function approximation methods have been studied in order to improve the learning speed and to solve the shortage of storage in the standard reinforcement learning algorithm of Q-Learning. Most function approximation methods remove some special quality of reinforcement learning and need prior knowledge and preprocessing. Fuzzy Q-Learning needs preprocessing to define fuzzy variables and Local Weighted Regression uses training examples. In this paper, we propose a function approximation method, Fuzzy Q-Map that is based on on-line fuzzy clustering. Fuzzy Q-Map classifies a query state and predicts a suitable action according to the membership degree. We applied the Fuzzy Q-Map, CMAC and LWR to the mountain car problem. Fuzzy Q-Map reached the optimal prediction rate faster than CMAC and the lower prediction rate was seen than LWR that uses training example.
Modeling a Multi-Agent based Web Mining System on the Hierarchical Web Environment
Yoon, Hee-Byung ; Kim, Hwa-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 643~648
DOI : 10.5391/JKIIS.2003.13.6.643
In order to provide efficient retrieving results for user query on the web environment, the various searching algorithms have developed and considered user`s preference and convenience. However, the searching algorithms are developed on the horizontal and non hierarchical web environment in general and could not apply to the complex hierarchical and functional web environments such like the enterprise network. In this paper, we purpose the multi-agent based web mining system which can provide the efficient mining results to the user on the special web environment. For doing this, we suggest the network model with the hierarchical web environment and model the multi agent based web mining system which has four corporation agents and fourteen process modules. Then, we explain the detailed functions of each agent considered the hierarchical environment according to the module. Especially, we purpose the new merging agent and improved ranking algorithm by using the graph theory.
Threshold Selection Method Based on the Distribution of Gray Levels
Kwon, Soon-H. ; Son, Seo-H. ; Bae, Jong-I. ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 649~654
DOI : 10.5391/JKIIS.2003.13.6.649
Most of the conventional image thresholding methods are based on the histogram function of the gray values. In this paper, we present a simple but effective example showing that the histogram-based thresholding methods do not perform well. To overcome the difficulty, the authors propose a new gray level threshold selection method based on the distribution of gray levels in images. Finally, we provide simulation results showing the effectiveness of the proposed threshold selection method through several examples.
Import Vector Voting Model for Multi-pattern Classification
Choi, Jun-Hyeog ; Kim, Dae-Su ; Rim, Kee-Wook ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 655~660
DOI : 10.5391/JKIIS.2003.13.6.655
In general, Support Vector Machine has a good performance in binary classification, but it has the limitation on multi-pattern classification. So, we proposed an Import Vector Voting model for two or more labels classification. This model applied kernel bagging strategy to Import Vector Machine by Zhu. The proposed model used a voting strategy which averaged optimal kernel function from many kernel functions. In experiments, not only binary but multi-pattern classification problems, our proposed Import Vector Voting model showed good performance for given machine learning data.
A Fuzzy Clustering Algorithm for Clustering Categorical Data
Kim, Dae-Won ; Lee, Kwang-H. ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 661~666
DOI : 10.5391/JKIIS.2003.13.6.661
In this paper, the conventional k-modes and fuzzy k-modes algorithms for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. The hard-type centroids of the traditional algorithms had difficulties in dealing with ambiguous boundary data, which might be misclassified and lead to thelocal optima. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. The distance measure between data and fuzzy centroids is more precise and effective than those of the k-modes and fuzzy k-modes. To test the proposed approach, the proposed algorithm and two conventional algorithms were used to cluster three categorical data sets. The proposed method was found to give markedly better clustering results.
Intelligent Digital Redesign for Dynamical Systems with Uncertainties
Cho, Kwang-Lae ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 667~672
DOI : 10.5391/JKIIS.2003.13.6.667
In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.
Face Recognition Using Wavelet Coefficients and Hidden Markov Model
Lee, Kyung-Ah ; Lee, Dae-Jong ; Park, Jang-Hwan ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 673~678
DOI : 10.5391/JKIIS.2003.13.6.673
In this paper, we proposes a method for face recognition using HMM(hidden Markov model) and wavelet coefficients First, input images are compressed by using the multi-resolution analysis based on the discrete wavelet transform. And then, the wavelet coefficients obtained from each subband are used as feature vectors to construct the HMMs. In the recognition stage, we obtained higher recognition rate by summing of each recognition rate of wavelet subband. The usefulness of the proposed method was shown by comparing with conventional VQ and DCT-HMM ones. The experimental results show that the proposed method is more satisfactory than previous ones.
Fingerprint classification using the clustering of the orientation of the ridges
Park, Chang-Hee ; Yoon, Kyung-Bae ; Choi, Jun-Hyeog ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 679~685
DOI : 10.5391/JKIIS.2003.13.6.679
The cores and deltas of fingerprints designate the parts where the flow of the ridges change radically. Observations on the change of the orientation of the ridges around the cores and deltas enable us to guess the location of the cores and deltas. According]y clustering the orientation flowing to the same direction after doing research on the orientation of the ridges on the whole makes us see that the cores and deltas are shaping around the boundaries of the clustering area. It is also observed that The patterns of clustering of the orientation of the ridges classified as Arch, Tented Arch, Left loop, Right Loop and Whorl have its own characteristics respectively. In this paper the method of classifying the fingerprints effectively is proposed and proved its effectiveness by using the clustering of the orientation of the ridges, finding the cores of the fingerprints which don`t secure the deltas.
A Study on the Obstacle-Avoidance Walking Algorithm of a Biped Robot
Kim, Yong-Tae ; Lee, Eun-Seon ; Lee, He-Young ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 686~691
DOI : 10.5391/JKIIS.2003.13.6.686
In the paper, an intelligent biped walking robot that can overcome the obstacle is developed. Walking algorithms are designed based on the analysis of the human`s manner of walking. Infrared sensors are used to detect the obstacles in the working environment and the remote controller of the biped robot use a RF module. The experiment results show that the developed biped walking robot can perform the stable static walking, attention walking, rotation and side stepping to avoid the obstacle, and hurdling the obstacle using the distance correction algorithm that is designed based on the distance information between the biped robot and the obstacle.
Internet Based Tele-operation of the Autonomous Mobile Robot
Sim, Kwee-Bo ; Byun, Kwang-Sub ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 692~697
DOI : 10.5391/JKIIS.2003.13.6.692
The researches on the Internet based tole-operation have received increased attention for the past few years. In this paper, we implement the Internet based tele-operating system. In order to transmit robustly the surroundings and control information of the robot, we make a data as a packet type. Also in order to transmit a very large image data, we use PEG compressive algorithm. The central problem in the Internet based tele-operation is the data transmission latency or data-loss. For this specific problem, we introduce an autonomous mobile robot with a 2-layer fuzzy controller. Also, we implement the color detection system and the robot can perceive the object. We verify the efficacy of the 2-layer fuzzy controller by applying it to a robot that is equipped with various input sensors. Because the 2-layer fuzzy controller can control robustly the robot with various inputs and outputs and the cost of control is low, we hope it will be applied to various sectors.
Chaotic Speech Secure Communication Using Self-feedback Masking Techniques
Lee, Ik-Soo ; Ryeo, Ji-Hwan ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 698~703
DOI : 10.5391/JKIIS.2003.13.6.698
This paper presents analog secure communication system about safe speech transmission using chaotic signals. We applied various conditions that happen in actuality communication environment modifying chaotic synchronization and chaotic communication schemes and analyzed restoration performance of speech signal to computer simulation. In transmitter, we made the chaotic masking signal which is added voice signal to chaotic signal using PC(Pecora ＆ Carroll) and SFB(self-feedback) control techniques and transmitted encryption signal to noisy communication channel And in order to calculate the degree of restoration performance, we proposed the definition of analog average power of recovered error signals in receiver chaotic system. The simulation results show that feedback control techniques can certify that restoration performance is superior to quantitative data than PC method about masking degree, susceptibility of parameters and channel noise. We experimentally computed the table of relation of parameter fluxion to restoration error rate which is applied the encryption key values to the chaotic secure communication.
A study on image edge detection using adaptive morphology Meyer wavelet-CNN
Beak, Young-Hyun ; Moon, Sung-Rung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 704~709
DOI : 10.5391/JKIIS.2003.13.6.704
The digital image can be distorted by a noise for a transmission or other elements of system. It happen to be vague of a boundary side in the division of an image object, especially, boundary side of an input image is very important because it can be determined to the division and detection element in pattern recognition. Therefore it is proposed an edge detection method of optimal to divide and detect exactly a boundary part. In this paper, it detected the optimal edge with applying this image to Meyer wavelet-CNN algorithm, after it does level up a boundary side of an image by using the adaptive morphology as the threshold of an input image. It confirmed that the proposed algorithm is more superior to the conventional methods and the conventional Sobel method which is an image edge detection algorithm. Especially, it is confirmed by simulation that the proposed algorithm can be got the better result edge at the place of closing to each edges and having smoothly curved line.
Emotion Recognition Using Template Vector and Neural-Network
Joo, Young-Hoon ; Oh, Jae-Heung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 710~715
DOI : 10.5391/JKIIS.2003.13.6.710
In this paper, we propose the new emotion recognition method for intelligently recognizing the human`s emotion using the template vector and neural network. In the proposed method, human`s emotion is divided into four emotion (surprise, anger, happiness, sadness). The proposed method is based on the template vector extraction and the template location recognition by using the color difference. It is not easy to extract the skin color area correctly using the single color space. To solve this problem, we propose the extraction method using the various color spaces and using the each template vectors. And then we apply the back-propagation algorithm by using the template vectors among the feature points). Finally, we show the practical application possibility of the proposed method.
Iris Recognition Using the 2-D Gabor Filter
Go, Hyoun-Joo ; Lee, Dae-Jong ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 716~721
DOI : 10.5391/JKIIS.2003.13.6.716
This paper deals with the iris recognition as one of biometric techniques which are applied to identify a person using his/her behavior or congenital characteristics. The iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D iris pattern having a property of size invariant and divide it into 24 sectors which are further through three types of 2D Gabor filters. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use three different matching values obtained from three different directional Gabor filters and select the maximum value among them, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 50 iris patterns extracted from 10 subjects and finally get more higher than 90% recognition rate.
A Fuzzy Traffic Controller Considering the spillback on the Multiple Crossroads
Kim, Young-Sik ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 722~728
DOI : 10.5391/JKIIS.2003.13.6.722
In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.
Chaotic behavior analysis in the mobile robot of embedding some chaotic equation with obstacle
Bae, Youngchul ; Kim, Juwan ; Kim, Yigon ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 729~736
DOI : 10.5391/JKIIS.2003.13.6.729
In this paper, we propose that the chaotic behavior analysis in the mobile robot of embedding some chaotic such as Chua`s equation, Arnold equation with obstacle. In order to analysis of chaotic behavior in the mobile robot, we apply not only qualitative analysis such as time-series, embedding phase plane, but also quantitative analysis such as Lyapunov exponent In the mobile robot with obstacle. We consider that there are two type of obstacle, one is fixed obstacle and the other is VDP obstacle which have an unstable limit cycle. In the VDP obstacles case, we only assume that all obstacles in the chaos trajectory surface in which robot workspace has an unstable limit cycle with Van der Pol equation.
Wavelet-Based Fuzzy Modeling Using a DNA Coding Method
Joo, Young-Hoon ; Lee, Yeun-Woo ; Yu, Jin-Young ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 737~742
DOI : 10.5391/JKIIS.2003.13.6.737
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 information based on the biological DNA. The proposed method makes a fuzzy model by using the wavelet transform, in which coefficients are identified by the DNA coding method. Thus we can effectively get the fuzzy model of 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 the GA.
RDB-based Automatic Knowledge Acquisition and Forward Inference Mechanism for Self-Evolving Expert Systems
Kim, Jin-Sung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 743~748
DOI : 10.5391/JKIIS.2003.13.6.743
In this research, we propose a mechanism to develop an inference engine and expert systems based on relational database (RDB) and SQL (structured query language). Generally, former researchers had tried to develop an expert systems based on text-oriented knowledge base and backward/forward (chaining) inference engine. In these researches, however, the speed of inference was remained as a tackling point in the development of agile expert systems. Especially, the forward inference needs more times than backward inference. In addition, the size of knowledge base, complicate knowledge expression method, expansibility of knowledge base, and hierarchies among rules are the critical limitations to develop an expert system. To overcome the limitations in speed of inference and expansibility of knowledge base, we proposed a relational database-oriented knowledge base and forward inference engine. Therefore, our proposed mechanism could manipulate the huge size of knowledge base efficiently. and inference with the large scaled knowledge base in a short time. To this purpose, we designed and developed an SQL-based forward inference engine using relational database. In the implementation process, we also developed a prototype expert system and presented a real-world validation data set collected from medical diagnosis field.
The Properties on Fuzzy Submachines of a Fuzzy Finite State Machine
Hwang, Seok-Yoon ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 749~753
DOI : 10.5391/JKIIS.2003.13.6.749
In this paper we introduce the concepts on retrievability, separability and connectedness of fuzzy submachines, which generalize those of crisp submachines. And also we generalize crisp primary submachines to those with fuzziness, from which we obtain the decomposition theorem of fuzzy submachines.
Strong laws of large numbers for tight fuzzy random variables
Kim, Yun-Kyong ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 6, 2003, Pages 754~758
DOI : 10.5391/JKIIS.2003.13.6.754
The present paper establishes a strong law of large numbers for sums of tight fuzzy random variables as a generalization of SLLN for sums of independent and identically distributed fuzzy random variables.