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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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An Implementation of the Controller Design System Using the Runge Kutta Method and Genetic Algorithms
Lee, Chung-Ki ; Kang, Hwan-Il ; Yu, Il-Kyu ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 259~259
DOI : 10.5391/JKIIS.2003.13.3.259
Genetic algorithms using a Process of genetic evolution of an organism are appropriate for hard problems that have not been solved by any deterministic method. Up to now, the controller design method has been made with the frequency dependent specification but the design method with the time specification has gotten little progress. In this paper, we study the controller design to satisfy the performance of a plant using the generalized Manabe standard form. When dealing with a controller design in the case of two parameter configurations, there are some situations that neither a known pseudo inverse technique nor the inverse method can be applicable. In this case, we propose two methods of designing a controller by the gradient algorithm and the new pseudo inverse method so that the desired closed polynomials are either equalized to or approximated to the designed polynomial. Design methods of the proposed controller are implemented in Java.
Support Vector Learning for Abnormality Detection Problems
Park, Joo-Young ; Leem, Chae-Hwan ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 266~274
DOI : 10.5391/JKIIS.2003.13.3.266
This paper considers an incremental support vector learning for the abnormality detection problems. One of the most well-known support vector learning methods for abnormality detection is the so-called SVDD(support vector data description), which seeks the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to modify the SVDD into the direction of utilizing the relation between the optimal solution and incrementally given training data. After a thorough review about the original SVDD method, this paper establishes an incremental method for finding the optimal solution based on certain observations on the Lagrange dual problems. The applicability of the presented incremental method is illustrated via a design example.
Emotion Recognition Using Output Data of Image and Speech
Joo, Young-Hoon ; Oh, Jae-Heung ; Park, Chang-Hyun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 275~280
DOI : 10.5391/JKIIS.2003.13.3.275
In this paper, we propose a method for recognizing the human s emotion using output data of image and speech. The proposed method is based on the recognition rate of image and speech. In case that we use one data of image or speech, it is hard to produce the correct result by wrong recognition. To solve this problem, we propose the new method that can reduce the result of the wrong recognition by multiplying the emotion status with the higher recognition rate by the higher weight value. To experiment the proposed method, we suggest the simple recognizing method by using image and speech. Finally, we have shown the potentialities through the expriment.
Patterns Recognition Using Translation-Invariant Wavelet Transform
Kim, Kuk-Jin ; Cho, Seong-Won ; Kim, Jae-Min ; Lim, Cheol-Su ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 281~286
DOI : 10.5391/JKIIS.2003.13.3.281
Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.
2-Layer Fuzzy Controller for Behavior Control of Mobile Robot
Sim, Kwee-Bo ; Byun, Kwang-Sub ; Park, Chang-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 287~292
DOI : 10.5391/JKIIS.2003.13.3.287
The ability of robot is being various and complex. The robot is utilizing distance, image data and voice data for sensing its circumstance. This paper suggests the 2-layer fuzzy control as the algorithm that control robot with various sensor information. In a obstacle avoidance, it utilizes many range finders and classifies them into 3parts(front, left, right). In 3 sub-controllers, the controller executes fuzzy conference. And then it executes combined control with a combination of outputs of 3 sub-controllers in the second step. The text compares the 2-layer fuzzy controller with the hierarchical fuzzy controller that has analogous structure. And the performance of the 2-layer fuzzy controller is confirmed by application this controller to robot following, simulation to each other and real experiment.
Design of Intelligent Controller with Time Delay for Internet-Based Remote Control
Joo, Young-Hoon ; Kim, Jung-Chan ; Lee, Oh-Jae ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 293~299
DOI : 10.5391/JKIIS.2003.13.3.293
This paper discusses a design of intelligent controller with time delay for Internet-based remote control. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The Takagi-Sugeno (T-S) fuzzy system with uncertain input delay is utilized to represent nonlinear plant. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The robust stochastic stabilizibility of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). An experimental results is provided to visualize the feasibility of the proposed method.
Forecasting of Traffic Situation using Internet
Hong, You-Sik ; Choi, Myeong-Bok ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 300~309
DOI : 10.5391/JKIIS.2003.13.3.300
The Japanese developed the first Car navigation system in 1981 with the advent of Honda, which was known as the car inertial navigation system. Now days, It is possible to search the shortest route to and from places and arrival time using the internet via cell phone to the driver based on GIS and GPS. However, even with a good navigation system, it losses the shortest route when there is an average speed of the vehicle being between S-15 kilometers. Therefore, in order to improve the vehicle waiting time and average vehicle speed, we are suggesting an optimal green time algorithm using fuzzy adaptive control, where there are different traffic intersection lengths, and lanes. In this paper, to be able to assist the driver and forecast the optimal traffic information with regards to the road conditions; dangerous roads, construction work and estimation of arrival time at their destination using internet.
Secure Communication using Embedding Drive Synchronization
Bae, Young-Chul ; Kim, Ju-Wan ; Kim, Yi-Gon ; Shon, Young-Woo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 310~315
DOI : 10.5391/JKIIS.2003.13.3.310
In this paper, We introduce an embedding driven synchronization method using SC-CNN(State-Controlled Cellular Neural Network) which has the purpose to secure communication method through the embedding driven synchronization method in the SC-CNN. we proposed new embedding driven synchronization that this method is only using one state variable compare to the general driven synchronization methods which is using all state variables. In this paper, We achieved the usage of embedding driven synchronization and we also applied it to secure communication.
Nu-SVR Learning with Predetermined Basis Functions Included
Kim, Young-Il ; Cho, Won-Hee ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 316~321
DOI : 10.5391/JKIIS.2003.13.3.316
Recently, support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. It is well-known that among the various support vector learning methods, the so-called no-versions are particularly useful in cases that we need to control the total number of support vectors. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and a no-version support vector learning called
. After reviewing
, and a semi-parametric approach, this paper presents an extension of the conventional
method toward the direction that can utilize Predetermined basis functions. Moreover, the applicability of the presented method is illustrated via an example.
Water Level Control of PWR Steam Generator using Knowledge Information and Neural Networks
Bae, Hyeon-Bae ; Woo, Young-Kwang ; Kim, Sung-Shin ; Jung, Kee-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 322~327
DOI : 10.5391/JKIIS.2003.13.3.322
The water level of a steam generator of pressurized light water nuclear Power generator is known as a subject whose control is difficult because of a shrinking and swelling effect that is been mutually contradictory in a variation of feed water. In this paper, a neural network model selects first coordinative controller by a inappropriate gain of two PI controllers and the selected controller＇s gain is tuned by a fuzzy self-tuner. Model inputs consist of the water level, the feed water, and the stream flow. One controller of both coupling controllers whose gain is handled firstly is decided based upon above data. The proposed method can analyze patterns of signals using the characteristic of neural networks and select one controller that needs to be tuned through the observed result in this paper. If one controller between both the water level controller and the feed water controller is selected by the neural network model then a gain of the PI controller is suitably tuned by the fuzzy self-tuner. Rules of the fuzzy self-tuner drew from the pattern of input and output data. In the summary, the goal of this Paper is to select the suitable controller and tune the control gain of the selected controller suitably through such two processes.
An Optimizing Hyperrectangle method for Nearest Hyperrectangle Learning
Lee, Hyeong-Il ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 328~333
DOI : 10.5391/JKIIS.2003.13.3.328
NGE (Nested Generalized Exemplars) proposed by Salzberg improved the storage requirement and classification rate of the Memory Based Reasoning. It constructs hyperrectangles during training and performs classification tasks. It worked not bad in many area, however, the major drawback of NGE is constructing hyperrectangles because its hyperrectangle is extended so as to cover the error data and the way of maintaining the feature weight vector. We proposed the OH (Optimizing Hyperrectangle) algorithm which use the feature weight vectors and the ED(Exemplar Densimeter) to optimize resulting Hyperrectangles. The proposed algorithm, as well as the EACH, required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the EACH. Also, by reducing the number of stored patterns, it showed excellent results in terms of classification when we compare it to the k-NN and the EACH.
Design and Implementation of Recurrent Time Delayed Neural Network Controller Using Fuzzy Compensator
Lee, Sang-Yun ; Shin, Woo-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 334~341
DOI : 10.5391/JKIIS.2003.13.3.334
In this paper, we proposed a recurrent time delayed neural network(RTDNN) controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network(TDU) controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.
Fuzzy Logic Based Prediction of Link Travel Velocity Using GPS Information
Jhong, Woo-Jin ; Lee, Jong-Soo ; Ko, Jin-Woong ; Park, Pyong-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 342~347
DOI : 10.5391/JKIIS.2003.13.3.342
It is essential to develop an algorithm for the estimate of link travel velocity and for the supply and control of travel information in the context of intelligent transportation information system. The paper proposes the fuzzy logic based prediction of link travel velocity. Three factors such as time, date and velocity are considered as major components to represent the travel situation. In the fuzzy modeling, those factors were expressed by fuzzy membership functions. We acquire position／velocity data through GPS antenna with PDA embedded probe vehicles. The link travel velocity is calculated using refined GPS data and the prediction results are compared with actual data for its accuracy.
Development of Advanced Personal Identification System Using Iris Image and Speech Signal
Lee, Dae-Jong ; Go, Hyoun-Joo ; Kwak, Keun-Chang ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 348~354
DOI : 10.5391/JKIIS.2003.13.3.348
This proposes a new algorithm for advanced personal identification system using iris pattern and speech signal. Since the proposed algorithm adopts a fusion scheme to take advantage of iris recognition and speaker identification, it shows robustness for noisy environments. For evaluating the performance of the proposed scheme, we compare it with the iris pattern recognition and speaker identification respectively. In the experiments, the proposed method showed more 56.7% improvements than the iris recognition method and more 10% improvements than the speaker identification method for high quality security level. Also, in noisy environments, the proposed method showed more 30% improvements than the iris recognition method and more 60% improvements than the speaker identification method for high quality security level.
Fuzzy semi-topogenous orders and fuzzy supra topologies
Kim, Yong-Chan ; Ko, Jung-Mi ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 355~359
DOI : 10.5391/JKIIS.2003.13.3.355
We investigate the properties of fuzzy (semi-)topogenous orders in the framework of fuzzy (supra) topologies and fuzzy (supra) interior operators. We study the relationship between fuzzy (semi-)topogenous structures, fuzzy (supra)topologies and fuzzy (supra)interior operators.
Development of Power Demand Forecasting Algorithm Using GMDH
Lee, Dong-Chul ; Hong, Yeon-Chan ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 360~365
DOI : 10.5391/JKIIS.2003.13.3.360
In this paper, GMDH(Croup Method of Data Handling) algorithm which is proved to be more excellent in efficiency and accuracy of practical use of data is applied to electric power demand forecasting. As a result, it became much easier to make a choice of input data and make an exact prediction based on a lot of data. Also, we considered both economy factors(GDP, export, import, number of employee, number of economically active population and consumption of oil) and climate factors(average temperature) when forecasting. We assumed target forecast period from first quarter 1999 to first quarter 2001, and suggested more accurate forecasting method of electric power demand by using 3-step computer simulation processes(first process for selecting optimum input period, second for analyzing time relation of input data and forecast value, and third for optimizing input data) for improvement of forecast precision. The proposed method can get 0.96 percent of mean error rate at target forecast period.
Hybrid Intelligent Web Recommendation Systems Based on Web Data Mining and Case-Based Reasoning
Kim, Jin-Sung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 366~370
DOI : 10.5391/JKIIS.2003.13.3.366
In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.
Facial Expression Recognition using ICA-Factorial Representation Method
Han, Su-Jeong ; Kwak, Keun-Chang ; Go, Hyoun-Joo ; Kim, Sung-Suk ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 371~376
DOI : 10.5391/JKIIS.2003.13.3.371
In this paper, we proposes a method for recognizing the facial expressions using ICA(Independent Component Analysis)-factorial representation method. Facial expression recognition consists of two stages. First, a method of Feature extraction transforms the high dimensional face space into a low dimensional feature space using PCA(Principal Component Analysis). And then, the feature vectors are extracted by using ICA-factorial representation method. The second recognition stage is performed by using the Euclidean distance measure based KNN(K-Nearest Neighbor) algorithm. We constructed the facial expression database for six basic expressions(happiness, sadness, angry, surprise, fear, dislike) and obtained a better performance than previous works.
Strong fuzzy hyperK-subalgebra
Kim, Y.H. ; Oh, K.A. ; Jeong, T.E. ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 3, 2003, Pages 377~379
DOI : 10.5391/JKIIS.2003.13.3.377
In this paper, we define a strong fuzzy hyperK-subalgebra and investigate between a strong fuzzy hyperK-subalgebra and a fuzzy hyperK-subalgebra. And then we give some properties of a weak homomorphism and a strong fuzzy hyperK-subalgebra.