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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 14, Issue 7 - Dec 2004
Volume 14, Issue 6 - Oct 2004
Volume 14, Issue 5 - Aug 2004
Volume 14, Issue 4 - Jul 2004
Volume 14, Issue 2 - Apr 2004
Volume 14, Issue 1 - Feb 2004
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Comparison of Interval-valued fuzzy sets, Intuitionistic fuzzy sets, and bipolar-valued fuzzy sets
Lee, Keon-Myung ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 125~129
DOI : 10.5391/JKIIS.2004.14.2.125
There are several kinds of fuzzy set extensions in the fuzzy set theory. Among them, this paper is concerned with interval-valued fuzzy sets, intuitionistic fuzzy sets, and bipolar-valued fuzzy sets. In interval-valued fuzzy sets, membership degrees are represented by an interval value that reflects the uncertainty in assigning membership degrees. In intuitionistic fuzzy sets, membership degrees are described with a pair of a membership degree and a nonmembership degree. In bipolar-valued fuzzy sets, membership degrees are specified by the satisfaction degrees to a constraint and its counter-constraint. This paper investigates the similarities and differences among these fuzzy set representations.
A Study of Short-Term Load Forecasting System Using Data Mining
Joo, Young-Hoon ; Jung, Keun-Ho ; Kim, Do-Wan ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 130~135
DOI : 10.5391/JKIIS.2004.14.2.130
This paper presents a new design methods of the short-term load forecasting system (STLFS) using the data mining. The structure of the proposed STLFS is divided into two parts: the Takagi-Sugeno (T-S) fuzzy model-based classifier and predictor The proposed classifier is composed of the Gaussian fuzzy sets in the premise part and the linearized Bayesian classifier in the consequent part. The related parameters of the classifier are easily obtained from the statistic information of the training set. The proposed predictor takes form of the convex combination of the linear time series predictors for each inputs. The problem of estimating the consequent parameters is formulated by the convex optimization problem, which is to minimize the norm distance between the real load and the output of the linear time series estimator. The problem of estimating the premise parameters is to find the parameter value minimizing the error between the real load and the overall output. Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.
A Scalable Clustering Method for Categorical Sequences
Oh, Seung-Joon ; Kim, Jae-Yearn ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 136~141
DOI : 10.5391/JKIIS.2004.14.2.136
There has been enormous growth in the amount of commercial and scientific data, such as retail transactions, protein sequences, and web-logs. Such datasets consist of sequence data that have an inherent sequential nature. However, few clustering algorithms consider sequentiality. In this paper, we study how to cluster sequence datasets. We propose a new similarity measure to compute the similarity between two sequences. We also present an efficient method for determining the similarity measure and develop a clustering algorithm. Due to the high computational complexity of hierarchical clustering algorithms for clustering large datasets, a new clustering method is required. Therefore, we propose a new scalable clustering method using sampling and a k-nearest-neighbor method. Using a real dataset and a synthetic dataset, we show that the quality of clusters generated by our proposed approach is better than that of clusters produced by traditional algorithms.
Automatic Determination of Usenet News Groups from User Profile
Kim, Jong-Wan ; Cho, Kyu-Cheol ; Kim, Hee-Jae ; Kim, Byeong-Man ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 142~149
DOI : 10.5391/JKIIS.2004.14.2.142
It is important to retrieve exact information coinciding with user`s need from lots of Usenet news and filter desired information quickly. Differently from email system, we must previously register our interesting news group if we want to get the news information. However, it is not easy for a novice to decide which news group is relevant to his or her interests. In this work, we present a service classifying user preferred news groups among various news groups by the use of Kohonen network. We first extract candidate terms from example documents and then choose a number of representative keywords to be used in Kohonen network from them through fuzzy inference. From the observation of training patterns, we could find the sparsity problem that lots of keywords in training patterns are empty. Thus, a new method to train neural network through reduction of unnecessary dimensions by the statistical coefficient of determination is proposed in this paper. Experimental results show that the proposed method is superior to the method using every dimension in terms of cluster overlap defined by using within cluster distance and between cluster distance.
Emotion Recognition Method from Speech Signal Using the Wavelet Transform
Go, Hyoun-Joo ; Lee, Dae-Jong ; Park, Jang-Hwan ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 150~155
DOI : 10.5391/JKIIS.2004.14.2.150
In this paper, an emotion recognition method using speech signal is presented. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. The proposed recognizer have each codebook constructed by using the wavelet transform for the emotional state. Here, we first verify the emotional state at each filterbank and then the final recognition is obtained from a multi-decision method scheme. The database consists of 360 emotional utterances from twenty person who talk a sentence three times for six emotional states. The proposed method showed more 5% improvement of the recognition rate than previous works.
A Coordinated Collaboration Method of Multiagent Systems based on Genetic Algorithms
Sohn, Bong-Ki ; Lee, Keon-Myung ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 156~163
DOI : 10.5391/JKIIS.2004.14.2.156
This paper is concerned with coordinated collaboration of multiagent system in which there exist multiple agents which have their own set of skills to perform some tasks, multiple external resources which can be either used exclusively by an agent or shared by the specified number of agents at a time, and a set of tasks which consists of a collection of subtasks each of which can be carried out by an agent. Even though a subtask can be carried out by several agents, its processing cost may be different depending on which agent performs it. To process tasks, some coordination work is required such as allocating their constituent subtasks among competent agents and scheduling the allocated subtasks to determine their processing order at each agent. This paper proposes a genetic algorithm-based method to coordinate the agents to process tasks in the considered multiagent environments. It also presents some experiment results for the proposed method and shows that the proposed method is a useful coordination collaboration method of multiagent system.
Distributed Autonomous Robotic System based on Artificial Immune system and Distributed Genetic Algorithm
Sim, Kwee-Bo ; Hwang, Chul-Min ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 164~170
DOI : 10.5391/JKIIS.2004.14.2.164
This paper proposes a Distributed Autonomous Robotic System(AIS) based on Artificial Immune System(AIS) and Distributed Genetic Algorithm(DGA). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: dispersion and aggregation. AIS decides one among above two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the DGA in the local. The proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.
Cognition-based Navigational Planning for Mobile Robots
Lee, In-K. ; Lee, Dong-J. ; Lee, Suk-Gyu ; Kwon, Soon-H. ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 171~177
DOI : 10.5391/JKIIS.2004.14.2.171
In this paper, we propose a cognition-based navigational algorithm for mobile robots in dynamic environments. The proposed algorithm consists of two main stages: (i) the fuzzy logic-based perception stage that constructs knowledge from the sensory data for subsequent usage in reasoning, and (ii) the planning stage that identifies the path between a starting and a goal position within its environment on the basis of the knowledge base on the environment and information from the perception stage. A mobile robot reasons places and moves to goal using ambiguous information and ambiguous knowledge through ‘perception’ and ‘planning’. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.
Hierarchical Fuzzy System with only system variables for IF-part
Joo, Moon-G. ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 178~183
DOI : 10.5391/JKIIS.2004.14.2.178
This paper presents a class of hierarchical fuzzy systems where previous layer outputs are used not in IF-parts, but only in THEN -parts of the fuzzy rules of the current layer. The existence of the proposed hierarchical fuzzy system which approximates a given real continuous function on a compact set is proven if complete fuzzy sets are used in the IF-parts of the fuzzy rules with singleton fuzzifier and center average defuzzifier
The Study on Dynamic Images Processing for Finger Languages
Kang, Min-Ji ; Choi, Eun-Sook ; Sohn, Young-Sun ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 184~189
DOI : 10.5391/JKIIS.2004.14.2.184
In this paper, we realized a system that receives the dynamic images of finger languages, which is the method of intention transmission of the hearing disabled person, using the white and black CCD camera, and that recognizes the images and converts them to the editable text document. We use the afterimage to draw a sharp line between indistinct images and clear images from a series of inputted images, and get the character alphabet from the away of continuous images and output the accomplished character to the word editor by applying the automata theory. After the system removes the varied wrist part from the data of clean image, it gets the controid point of hand by the maximum circular movement method and recognizes the hand that is necessary to analyze the finger languages by applying the circular pattern vector algorithm. The system abstracts the characteristic vectors of the hand using the distance spectrum from the center of the hand and it compares the characteristic vector of inputted pattern from the standard pattern by applying the fuzzy inference and recognizes the movement of finger languages.
Modeling of Nonlinear SBR Process for Nitrogen Removal Using Fuzzy Systems
Kim, Dong-Won ; Park, Jang-Hyun ; Lee, Ho-Sik ; Park, Young-Whan ; Park, Gwi-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 190~194
DOI : 10.5391/JKIIS.2004.14.2.190
This paper shows the application of fuzzy system for a modeling of nonlinear biochemical process. A wastewater treatment process for nitrogen removal in a sequencing batch reactor (SBR) is presented and fuzzy systems with different consequent polynomials in the fuzzy rules to model and identify the oxidation reduction potential (ORP) of the process are introduced. The paper compares, analyzes the results of fuzzy modeling, and shows the nonlinear process can be modeled reasonably well by the present scheme.
Boids′ Behavioral Modeling based Fuzzy Flocking
Kwon, Il-Kyoung ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 195~200
DOI : 10.5391/JKIIS.2004.14.2.195
Computer games use an intelligent method called flocking for boids` group behavioral modeling. Flocking can naturally model group behavioral patterns of unpredictable forms such as birds and fishes using some computer resource. In this paper, we implemented an ecosystem which is composed of predator and prey for group behavioral modeling of real underwater ecosystem. Also fuzzy logic is applied to implement instinct desire of ecosystem elements. As the result, we confirmed that the model can overcome breakdown of ecosystem and model naturally ecosystem behavior.
A Study on Design and Implementation of Embedded System for speech Recognition Process
Kim, Jung-Hoon ; Kang, Sung-In ; Ryu, Hong-Suk ; Lee, Sang-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 201~206
DOI : 10.5391/JKIIS.2004.14.2.201
This study attempted to develop a speech recognition module applied to a wheelchair for the physically handicapped. In the proposed speech recognition module, TMS320C32 was used as a main processor and Mel-Cepstrum 12 Order was applied to the pro-processor step to increase the recognition rate in a noisy environment. DTW (Dynamic Time Warping) was used and proven to be excellent output for the speaker-dependent recognition part. In order to utilize this algorithm more effectively, the reference data was compressed to 1/12 using vector quantization so as to decrease memory. In this paper, the necessary diverse technology (End-point detection, DMA processing, etc.) was managed so as to utilize the speech recognition system in real time
Development of an Intelligent Software Programmable Logic Controller for IEC1131-3 International Standard Languages
Cho, Young-Im ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 207~215
DOI : 10.5391/JKIIS.2004.14.2.207
The PLC programming by IEC1131-3 is hard to handle to ordinary users as well as professionals. Also it has not a generality, so that it couldn`t be debugging some logic errors easily. In order to be adapted for such environment, In this paper, I have developed the ISPLC(Intelligent Agent System based Software Programmable Logic Controller). In ISPLC system, LD programmed by a user is converted to the C code which can be used in a commercial editor such as Visual C++. The detection of logical errors in C code is more effective than PLC programming itself. ISPLC provides the GUI-based interface in web environment and an easy programming platform to such beginners as well as professionals. The study of code conversion of LD to IL as well as IL to C is firstly tried in the world as well as KOREA. To show the effectiveness of the developed system, I applied it to a practical case, a real time traffic control system. ISPLC is minimized the error debugging and programming time owing to be supported by windows application programs.
NETLA Based Optimal Synthesis Method of Binary Neural Network for Pattern Recognition
Lee, Joon-Tark ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 216~221
DOI : 10.5391/JKIIS.2004.14.2.216
This paper describes an optimal synthesis method of binary neural network for pattern recognition. Our objective is to minimize the number of connections and the number of neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm (NETLA) for the multilayered neural networks. The synthesis method in NETLA uses the Expanded Sum of Product (ESP) of the boolean expressions and is based on the multilayer perceptron. It has an ability to optimize a given binary neural network in the binary space without any iterative learning as the conventional Error Back Propagation (EBP) algorithm. Furthermore, NETLA can reduce the number of the required neurons in hidden layer and the number of connections. Therefore, this learning algorithm can speed up training for the pattern recognition problems. The superiority of NETLA to other learning algorithms is demonstrated by an practical application to the approximation problem of a circular region.
Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network
Kim, Kwang-Baek ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 222~227
DOI : 10.5391/JKIIS.2004.14.2.222
Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.
Optimal Design of the 2-Layer Fuzzy Controller using the Schema Co-Evolutionary Algorithm
Sim, Kwee-Bo ; Byun, Kwang-Sub ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 228~233
DOI : 10.5391/JKIIS.2004.14.2.228
Nowadays, the robot with various and complex functions is required. previous algorithms, however, cannot satisfy the requirement. In order to solve these problems, we introduce the 2-Layer Fuzzy Controller, which has a small number of fuzzy rules corresponding to various inputs and outputs. Also, it controls robustly and effectively an object. The main problem in the fuzzy controller is how to design the fuzzy rule. This paper designs the optimal 2-layer fuzzy controller using the Schema Co-Evolutionary Algorithm. The schema co-evolutionary algorithm can find more rapidly and excellently than simple genetic algorithm does.
Semiopen sets intuitionistic fuzzy topological spaces in Sostak′s sense
Lee, Eun-Pyo ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 234~238
DOI : 10.5391/JKIIS.2004.14.2.234
We introduce the concepts of fuzzy (r, s)-semiopen sets and fuzzy (r, s)-semicontinuous mappings on intuitionistic fuzzy topological spaces in Sostak`s sense and then we investigate some of their characteristic properties.
The Study of the Position Estimation for an Autonomous Land Vehicle
Lim, Ho ; Park, Chong-Kug ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 239~246
DOI : 10.5391/JKIIS.2004.14.2.239
In this paper, we develop and implement a high integrity GNC(Guidance, Navigation, and Control) system, based on the combined use of the Global Positioning System (GPS) and an Inertial Measurement Unit (IMU), for autonomous land vehicle applications. This paper highlights guidance for the predetermined trajectory and navigation with detection of possible faults during the fusion process in order to enhance the integrity of the navigation loop. The implementation of the GNC system to the autonomous land vehicle presented with fault detection methodology considers high frequency faults from the GPS receiver caused by shadowing and multipath error The implementation, based on a low-cost, strapdown INS aided by standard GPS technology, is described. The results of the field test in the urban environment are presented and showed effectiveness of the GNC system.
2nd-order PD-type Learning Control Algorithm
Kim, Yong-Tae ; Zeungnam Bien ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 2, 2004, Pages 247~252
DOI : 10.5391/JKIIS.2004.14.2.247
In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.