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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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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 8, Issue 4 - Dec 2008
Volume 8, Issue 3 - Sep 2008
Volume 8, Issue 2 - Jun 2008
Volume 8, Issue 1 - Mar 2008
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A Comparison Study of Classification Algorithms in Data Mining
Lee, Seung-Joo ; Jun, Sung-Rae ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 1~5
DOI : 10.5391/IJFIS.2008.8.1.001
Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.
An (r,s)-derived sets and double fuzzy closure operators
Zahran, Ahmed M. ; Abd-Allah, M. Azab ; EI-Saady, Kamal ; EI-Rahman, Abd EI-Nasser G. Abd ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 6~10
DOI : 10.5391/IJFIS.2008.8.1.006
In this paper, we introduce the concept of fuzzy (r, s)-adherence points, fuzzy (r, s)-accumulation points and fuzzy (r, s)-derived sets in double fuzzy topology. We investigate some of their properties. The relationship with double fuzzy closure operator was studied.
Application of Principal Components Analysis Method to Wireless Sensor Network Based Structural Monitoring Systems
Congyi, Zhang ; Mission, Jose Leo ; Kim, Sung-Ho ; Youk, Yui-Su ; Kim, Hyeong-Joo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 11~17
DOI : 10.5391/IJFIS.2008.8.1.011
Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.
Application of Similarity Measure for Fuzzy C-Means Clustering to Power System Management
Park, Dong-Hyuk ; Ryu, Soo-Rok ; Park, Hyun-Jeong ; Lee, Sang-H. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 18~23
DOI : 10.5391/IJFIS.2008.8.1.018
A FCM with locational price and regional information between locations are proposed in this paper. Any point in a networked system has its own values indicating the physical characteristics of that networked system and regional information at the same time. The similarity measure used for FCM in this paper is defined through the system-wide characteristic values at each point. To avoid the grouping of geometrically distant locations with similar measures, the locational information are properly considered and incorporated in the proposed similarity measure. We have verified that the proposed measure has produced proper classification of a networked system, followed by an example of a networked electricity system.
Dynamic Simulation of AGC/LPC Synthetical System for Hot Strip Finishing Mill
Wang, Xiaoying ; Wang, Jingcheng ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 24~30
DOI : 10.5391/IJFIS.2008.8.1.024
A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.
Evolvable Neural Networks for Time Series Prediction with Adaptive Learning Interval
Seo, Sang-Wook ; Lee, Dong-Wook ; Sim, Kwee-Bo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 31~36
DOI : 10.5391/IJFIS.2008.8.1.031
This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.
Implicative Closure Operators
Kim, Yong-Chan ; Ko, Jung-Mi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 37~41
DOI : 10.5391/IJFIS.2008.8.1.037
In this paper, we investigate the properties of implicative closure operators on the stsc-quantale L. We find implicative closure operators induced by a function.
Inter-space Interaction Issues Impacting Middleware Architecture of Ubiquitous Pervasive Computing
Lim, Shin-Young ; Helal, Sumi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 42~51
DOI : 10.5391/IJFIS.2008.8.1.042
We believe that smart spaces, offering pervasive services, will proliferate. However, at present, those islands of smart spaces should be joined seamlessly with each other. As users move about, they will have to roam from one autonomous smart space to another. When they move into the new island of smart space, they should setup their devices and service manually or not have access to the services available in their home spaces. Sometimes, there will conflicts between users when they try to occupy the same space or use a specific device at the same time. It will also be critical to elder people who suffer from Alzheimer or other cognitive impairments when they travel from their smart space to other visited spaces (e.g., grocery stores, museums). Furthermore our experience in building the Gator Tech Smart House reveals to us that home residents generally do not want to lose or be denied all the features or services they have come to expect simply because they move to a new smart space. The seamless inter-space interaction requirements and issues are raised automatically when the ubiquitous pervasive computing system tries to establish the user`s service environment by allocating relevant resources after the user moves to a new location where there are no prior settings for the new environment. In this paper, we raise and present several critical inter-space interactions issues impacting middleware architecture design of ubiquitous pervasive computing. We propose requirements for resolving these issues on seamless inter-space operation. We also illustrate our approach and ideas via a service scenario moving around two smart spaces.
Modified Version of SVM for Text Categorization
Jo, Tae-Ho ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 52~60
DOI : 10.5391/IJFIS.2008.8.1.052
This research proposes a new strategy where documents are encoded into string vectors for text categorization and modified versions of SVM to be adaptable to string vectors. Traditionally, when the traditional version of SVM is used for pattern classification, raw data should be encoded into numerical vectors. This encoding may be difficult, depending on a given application area of pattern classification. For example, in text categorization, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and apply the modified version of SVM adaptable to string vectors for text categorization.
Multi-vehicle Route Selection Based on an Ant System
Kim, Dong-Hun ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 61~67
DOI : 10.5391/IJFIS.2008.8.1.061
This paper introduces the multi-vehicle routing problem(MRP) which is different from the traveling sales problem(TSP), and presents the ant system(AS) applied to the MRP. The proposed MRP is a distributive model of TSP since many vehicles are used, not just one salesman in TSP and even some constraints exist. In the AS, a set of cooperating agents called vehicles cooperate to find good solutions to the MRP. To make the proposed MRP extended more, Tokyo city model(TCM) is proposed. The goal in TCM is to find a set of routes that minimizes the total traveling time such that each vehicle can reach its destination as soon as possible. The results show that the AS can effectively find a set of routes minimizing the total traveling time even though the TCM has some constraints.
Neural Network Compensation Technique for Standard PD-Like Fuzzy Controlled Nonlinear Systems
Song, Deok-Hee ; Lee, Geun-Hyeong ; Jung, Seul ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 68~74
DOI : 10.5391/IJFIS.2008.8.1.068
In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.
On Top-Down Design of MPEG-2 Audio Encoder
Park, Sung-Wook ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 75~81
DOI : 10.5391/IJFIS.2008.8.1.075
This paper presents a top-down approach to implement an MPEG-2 audio encoder in VLSI. As the algorithm of an MPEG-2 audio encoder is heavy-weighted and heterogeneous(to be mixture of several strategies), the encoder design process is undertaken carefully from the algorithmic level to the architectural level. Firstly, the encoding algorithm is analyzed and divided into sub-algorithms, called tasks, and the tasks are partitioned in the way of reusing the same designs. Secondly, the partitioned tasks are scheduled and synthesized to make the most efficient use of time and space. In the end, a real-time 5 channel MPEG-2 audio encoder is designed which is a heterogeneous multiprocessor system; two hardwired logic blocks and one specialized DSP processor.
Unsupervised Real-time Obstacle Avoidance Technique based on a Hybrid Fuzzy Method for AUVs
Anwary, Arif Reza ; Lee, Young-Il ; Jung, Hee ; Kim, Yong-Gi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 8, issue 1, 2008, Pages 82~86
DOI : 10.5391/IJFIS.2008.8.1.082
The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.