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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 7, Issue 4 - Dec 2007
Volume 7, Issue 3 - Sep 2007
Volume 7, Issue 2 - Jun 2007
Volume 7, Issue 1 - Mar 2007
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A Particle Filtering Approach for On-Line Failure Prognosis in a Planetary Carrier Plate
Orchard, Marcos E. ; Vachtsevanos, George J. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 221~227
DOI : 10.5391/IJFIS.2007.7.4.221
This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.
A Study on 3D RTLS at Port Container Yards Using the Extended Kalman Filter
Kim, Joeng-Hoon ; Lee, Hyun-Woo ; Kwon, Soon-Ryang ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 228~235
DOI : 10.5391/IJFIS.2007.7.4.228
The main purpose of this paper is to manage the container property effectively at the container yard by applying the RTLS technology to the field of port logistics. Yet, many kinds of noises happen to be inputted with the distance value(between the reader and the tag) which is to be inputted into the location identification algorithm, which makes the distance value jumped due to the system noise of the ultrasonic sensor module and the measurement noise. The Kalman Filter is widely used to prevent this jump occurrence; the noises are eliminated by using the EKF(Extended Kalman Filter) while considering that the distance information of the ultrasonic sensor is non-linear. Also, the 3D RTLS system at the port container yard suggested in this research is designed not to be interrupted for its ultrasonic transmission by positioning the antenna at the front of each sector of the container where the active tags are installed. We positioned the readers, which function as antennas for location identification, to four places randomly in the absolute coordinate and let the positions of the active tags identified by using the distance data delivered from the active tags. For the location identification algorithm used in this paper, the triangulation measurement that is most used in general is applied and newly reorganized to calculate the position of the container. In the first experiment, we dealt with the error resulting in the angle and the distance of the ultrasonic sensor module, which is the most important in the hardware performance; in the second, we evaluated the performance of the location identification algorithm, which is the most important in the software performance, and tested the noise cancellation effects for the EKF. According to the experiment result, the ultrasonic sensor showed an average of 3 to 5cm error up to
in case of
or more, non-reliable linear distances were obtained. In addition, the evaluation of the algorithm performance showed an average of
error due to the error of the linear distance-this error is negligible for most container location identifications. Lastly, the experiment results of noise cancellation and jump preservation by using the EKF showed that noises were removed in the distance information which was entered from the input of the ultrasonic sensor and as a result, only signal was extracted; thus, jumps were able to be removed and the exact distance information between the ultrasonic sensors could be obtained.
A study on the Adaptive Controller with Chaotic Dynamic Neural Networks
Kim, Sang-Hee ; Ahn, Hee-Wook ; Wang, Hua O. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 236~241
DOI : 10.5391/IJFIS.2007.7.4.236
This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.
A study on the Convergence Condition of Chaotic Dynamic Neural Networks
Kim, Sang-Hee ; Wang, Hua O. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 242~248
DOI : 10.5391/IJFIS.2007.7.4.242
This paper analyzes on the chaos characteristics of the chaotic neural networks and presents the convergence condition. Although the transient chaos of neural network sould be beneficial to overcome the local minimum problem and speed up the learning, the permanent chaotic response gives adverse effect on optimization problems and makes neural network unstable in general. This paper investigates the dynamic characteristics of the chaotic neural networks with the chaotic dynamic neuron, and presents the convergence condition for stabilizing the chaotic neural networks.
Double Fuzzy Preproximity Spaces
Zahran, Ahmed M. ; Abd-Allah, M. Azab ; El-Saady, Kamal ; El-Rahman, Abd El-Nasser G. Abd ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 249~255
DOI : 10.5391/IJFIS.2007.7.4.249
In this paper, we introduce the concept of double fuzzy preproximity spaces as a generalization of a fuzzy preproximity spaces and investigate some of their properties. Also we study the relationships between double fuzzy preproximity spaces, double fuzzy topological spaces and double fuzzy closure spaces. In addition to this was the introduction of the concept of double fuzzy neighborhood system and has been studying the connection with double fuzzy preproximity, which resulted in the definition of the concept double fuzzy preproximal neighborhood.
Emotion Recognition Method for Driver Services
Kim, Ho-Duck ; Sim, Kwee-Bo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 256~261
DOI : 10.5391/IJFIS.2007.7.4.256
Electroencephalographic(EEG) is used to record activities of human brain in the area of psychology for many years. As technology developed, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study Emotion Recognition method which uses one of EEG signals and Gestures in the existing research. In this paper, we use together EEG signals and Gestures for Emotion Recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both EEG signals and gestures gets high recognition rates better than using EEG signals or gestures. Both EEG signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on the reinforcement learning.
Fuzzy pairwise γ-irresoluteness
Im, Young-Bin ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 262~266
DOI : 10.5391/IJFIS.2007.7.4.262
We characterize a fuzzy pairwise
-irresolute continuous mapping on a fuzzy bitopological space.
Implementation and Experiment of Neural Network Controllers for Intelligent Control System Education
Lee, Geun-Hyeong ; Noh, Jin-Seok ; Jung, Seul ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 267~273
DOI : 10.5391/IJFIS.2007.7.4.267
This paper presents the implementation of an educational kit for intelligent system control education. Neural network control algorithms are presented and control hardware is embedded to control the inverted pendulum system. The RBF network and the MLP network are implemented and embedded on the DSP 2812 chip and other necessary functions are embedded on an FPGA chip. Experimental studies are conducted to compare performances of two neural control methods. The intelligent control educational kit(ICEK) is implemented with the inverted pendulum system whose movements of the cart is limited by space. Experimental results show that the neural controllers can manage to control both the angle and the position of the inverted pendulum systems within a limited distance. Performances of the RCT and the FEL control method are compared as well.
On supporting full-text retrievals in XML query
Hong, Dong-Kweon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 274~278
DOI : 10.5391/IJFIS.2007.7.4.274
As XML becomes the standard of digital data exchange format we need to manage a lot of XML data effectively. Unlike tables in relational model XML documents are not structural. That makes it difficult to store XML documents as tables in relational model. To solve these problems there have been significant researches in relational database systems. There are two kinds of approaches: 1) One way is to decompose XML documents so that elements of XML match fields of relational tables. 2) The other one stores a whole XML document as a field of relational table. In this paper we adopted the second approach to store XML documents because sometimes it is not easy for us to decompose XML documents and in some cases their element order in documents are very meaningful. We suggest an efficient table schema to store only inverted index as tables to retrieve required data from XML data fields of relational tables and shows SQL translations that correspond to XML full-text retrievals. The functionalities of XML retrieval are based on the W3C XQuery which includes full-text retrievals. In this paper we show the superiority of our method by comparing the performances in terms of a response time and a space to store inverted index. Experiments show our approach uses less space and shows faster response times.
On-line Diagnosis System with Learning Bayesian Networks for fsEBPR
Cheon, Seong-Pyo ; Kim, Sung-Shin ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 279~284
DOI : 10.5391/IJFIS.2007.7.4.279
Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operator's absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuosly update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.
Online Parameter Estimation and Convergence Property of Dynamic Bayesian Networks
Cho, Hyun-Cheol ; Fadali, M. Sami ; Lee, Kwon-Soon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 285~294
DOI : 10.5391/IJFIS.2007.7.4.285
In this paper, we investigate a novel online estimation algorithm for dynamic Bayesian network(DBN) parameters, given as conditional probabilities. We sequentially update the parameter adjustment rule based on observation data. We apply our algorithm to two well known representations of DBNs: to a first-order Markov Chain(MC) model and to a Hidden Markov Model(HMM). A sliding window allows efficient adaptive computation in real time. We also examine the stochastic convergence and stability of the learning algorithm.
Similarity Analysis Between Fuzzy Set and Crisp Set
Park, Hyun-Jeong ; Lee, Sang-Hyuk. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 295~300
DOI : 10.5391/IJFIS.2007.7.4.295
The similarity analysis for fuzzy set pair or crisp set pair are carried out. The similarity measure that is based on distance measure is derived and proved. The proposed similarity measure is considered with the help of analysis for uncertainty or certainty part of the membership functions. The usefulness of proposed similarity is verified through the computation of similarity between fuzzy set and crisp set or fuzzy set and fuzzy set. Our results are also compared with those of previous similarity measure which is based on fuzzy number.
Time Variant Event Ontology for Temporal People Information
Han, Yong-Jin ; Park, Se-Young ; Park, Seong-Bae ; Lee, Young-Hwa ; Kim, Kweon-Yang ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 7, issue 4, 2007, Pages 301~306
DOI : 10.5391/IJFIS.2007.7.4.301
The people information is distributed in various forms such as database, web page, text, and so on, where the world wide web is one of the main sources of publicly-available people information. It has a characteristic that the information on people is intrinsically temporal. Therefore, the reconstruction of the information is needed for an individual or a company to use it efficiently. In order to maintain or manage the temporal people information, it must distinguish the variable information from invariable information of people. In this paper, we propose a method that constructs an ontology based on events to manage the variable people information efficiently. In addition, we present a system which reconstructs people information that satisfies the users' demand with the ontology.