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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 1, Issue 1 - Jun 2001
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A Fuzzy Traffic Controller Considering Spillback on Crossroads
Park, Wan-Kyoo ; Lee, Sung-Joo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 1~5
In this paper, we propose a fuzzy traffic controller that is able to cope with traffic congestion appropriately. In order to consider such situation as loss of green time caused by spillback of upper crossroad, it imports a degree of traffic congestion of upper roads which vehicles on a crossroad are to proceed to. We constructed the equal-partitioned fuzzy traffic controller that uses the membership functions of the same size and shape, and modified the size and shape, and modified the size and shape of its membership functions by the membership function modification algorithm. In experiment, we compared and analyzed the fixed signal controller, the fuzzy traffic controller with the membership of the same size and shape, and the modified fuzzy traffic controller by using the delay time, the proportion of entered vehicles to occurred vehicles and the proportion of passed vehicles to entered vehicles. As a result of experiment, the modified fuzzy controller showed more enhanced performance than others.
A Hybrid of Evolutionary Search and Local Heuristic Search for Combinatorial Optimization Problems
Park, Lae-Jeong ; Park, Cheol-Hoon ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 6~12
Evolutionary algorithms(EAs) have been successfully applied to many combinatorial optimization problems of various engineering fields. Recently, some comparative studies of EAs with other stochastic search algorithms have, however, shown that they are similar to, or even are not comparable to other heuristic search. In this paper, a new hybrid evolutionary algorithm utilizing a new local heuristic search, for combinatorial optimization problems, is presented. The new intelligent local heuristic search is described, and the behavior of the hybrid search algorithm is investigated on two well-known problems: traveling salesman problems (TSPs), and quadratic assignment problems(QAPs). The results indicate that the proposed hybrid is able to produce solutions of high quality compared with some of evolutionary and simulated annealing.
A Knowledge-Based Machine Vision System for Automated Industrial Web Inspection
Cho, Tai-Hoon ; Jung, Young-Kee ; Cho, Hyun-Chan ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 13~23
Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.
A Study on the Performance of the Watermarking with Wavelet Transform
Kang, Hwan-Il ; Park, Hwan-soo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 24~28
Wavelet transforms are used for implementing digital watermarking methods in the frequency domain. In this paper, we construct the digital watermarking using various wavelet transforms such as the Daubechies transform, Coiflets transform, Symlets transform and the biorthogonal transform, and we compare each digital watermarking method with the others. We investigate the preservation of the watermark after the data compression attack based on the discrete on the discrete cosine transform. We show that the biorthogonal wavelet, denoted by bior3.5, has the best performance among the wavelet types we selected in an experiment.
Control of Flexible Joint Robot Using Direct Adaptive Neural Networks Controller
Lee, In-Yong ; Tack, Han-Ho ; Lee, Sang-Bae ; Park, Boo-Kwi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 29~34
This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.
Design of GBSB Neural Network Using Solution Space Parameterization and Optimization Approach
Cho, Hy-uk ; Im, Young-hee ; Park, Joo-young ; Moon, Jong-sup ; Park, Dai-hee ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 35~43
In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.
Design of Single-input Direct Adaptive Fuzzy Logic Controller Based on Stable Error Dynamics
Park, Byung-Jae ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 44~49
For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.
Fuzzy c-Continuous Mappings
Hur, K. ; Ryon, J.H. ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 50~55
We generalize mainly the concept of c-continuity of a mapping due to Gentry and Hoyle III in fuzzy setting. And we investigate some properties of fuzzy c-continuous mappings.
Modeling, Control, and Optimization of Activated Sludge Processes
Bae, Hye-on ; Kim, Bong-chul ; Kim, Sung-shin ; Kim, Chang-won ; Kim, Sang-hyun ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 56~61
Activated sludge processes are broadly used in the biological wastewater treatment processes. The activated sludge processes are complex systems because of the many factors such as the variation of influent flowrate and ingredients, the complexity of biological reactions, and the various operation conditions. The main motivation o this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system owing to the characteristic of wastewater, the change in influent flowrate, weather conditions, and so on. The mathematical model of ASP also includes the uncertainty which is a ignored or unconsidered factor from process designers. The ASP model based on Matlabⓡ/Simulinkⓡ is developed in this paper. And the model performance is examined by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data. The model tests derive steady-state results of 14 days. In this paper, fuzzy logic control approach is applied to handle DO concentrations. The fuzzy logic controller includes two inputs and one output to adjust air flowrate. The objective function for the optimization, in the implemented evolutionary strategy, is formed with focusing on improving the effluent quality and reducing the operating cost.
Fuzzy r-Pre-semineighborhoods and Fuzzy r-Pre-semicontinuous Maps
Lee, Seok-Jong ; Eoum, Youn-Suk ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 62~68
In this paper, we introduce the concepts of fuzzy r-pre-semiopen and r-pre-semiclosed sets. With them we define fuzzy r-pre-semiinterior and r-pre-semiclosure. We also introduce and investigate the properties of a fuzzy r-pre-semicontinuous map, a fuzzy r-pre-semiopen map and a fuzzy r-pre-semiclosed map. These concepts are generalizations of the Bai Shi-Zhongs fuzzy pre-semicontinuity
Fuzzy semi-regular spaces and fuzzy
Kim, Yong-Chan ; Ko, Jung-Mi ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 69~74
We introduce fuzzy semi-regular spaces. Furthermore, we investigate the relations among fuzzy super continuity, fuzzy
-continuity and fuzzy almost continuity in fuzzy topological spaces in view of the definition of Sostak. We study some properties between them.
Inconsistency in Fuzzy Rulebase: Measure and Optimization
Shounak Roychowdhury ; Wang, Bo-Hyeun ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 75~80
Rule inconsistency is an important issue that is needed to be addressed while designing efficient and optimal fuzzy rule bases. Automatic generation of fuzzy rules from data sets, using machine learning techniques, can generate a significant number of redundant and inconsistent rules. In this study we have shown that it is possible to provide a systematic approach to understand the fuzzy rule inconsistency problem by using the proposed measure called the Commonality measure. Apart from introducing this measure, this paper describes an algorithm to optimize a fuzzy rule base using it. The optimization procedure performs elimination of redundant and/or inconsistent fuzzy rules from a rule base.
Modeling of Bank Asset Management System based on Intelligent Agent
Kim, Dae-Su ; Kim, Chang-Suk ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 81~86
In this paper, we investigated the modeling of Bank Asset Management System(BAME) based on intelligent agent. To achieve this goal, we introduced several kinds of agents that show intelligent features. BAMS is a user friendly system and adopts fuzzy converting system and fuzzy matching system that returns reasonable similarity matching results. Generation function of the proximity degree is suggested. Fuzzification of investment type categories and feature values are defined, and generation of proximity degree is also derived. An example of bank asset management system is introduced and simulated. Investment type matching utilizing fuzzy measure is tested and it showed quite reasonable similarity matching results.
Neural Network Modeling of PECVD SiN Films and Its Optimization Using Genetic Algorithms
Han, Seung-Soo ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 87~94
Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.
Neural Network Tuning of the 2-DOF PID Controller With a Combined 2-DOF Parameter For a Gas Turbine Generating Plant
Kim, Dong-Hwa ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 95~103
The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.
Nonlinear Time Series Analysis Tool and its Application to EEG
Kim, Eung-Soo ; Park, Kyung-Gyu ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 104~112
Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.
Optimal Intelligent Digital Redesign for a Class of Fuzzy-Model-Based Controllers
Chang-wook ; Joo, Young-hoon ; Park, Jin-bae ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 113~118
In this paper, we develop an optimal intelligent digital redesign method for a class of fuzzy-model-based controllers, effective for stabilization of continuous-time complex nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to extend the results of the classical digital redesign technique to complex nonlinear systems. Unlike the conventional intelligent digital redesign technique reported in the literature, the proposed method utilized the recently developed LMI optimization technique to obtain a digitally redesigned fuzzy-model-based controller. Precisely speaking, the intelligent digital redesign problem is converted to an equivalent optimization problem, and the LMI optimization method is used to find the digitally redesigned fuzzy-model-based controller. A numerical example is provided to evaluate the feasibility of the proposed approach.
Parallel Fuzzy Inference Method for Large Volumes of Satellite Images
Lee, Sang-Gu ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 119~124
In this pattern recognition on the large volumes of remote sensing satellite images, the inference time is much increased. In the case of the remote sensing data  having 4 wavebands, the 778 training patterns are learned. Each land cover pattern is classified by using 159, 900 patterns including the trained patterns. For the fuzzy classification, the 778 fuzzy rules are generated. Each fuzzy rule has 4 fuzzy variables in the condition part. Therefore, high performance parallel fuzzy inference system is needed. In this paper, we propose a novel parallel fuzzy inference system on T3E parallel computer. In this, fuzzy rules are distributed and executed simultaneously. The ONE_To_ALL algorithm is used to broadcast the fuzzy input to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of the fuzzy rules, the parallel fuzzy inference algorithm extracts match parallelism and achieves a good speed factor. This system can be used in a large expert system that ha many inference variables in the condition and the consequent part.
Performance Improvement of Evolution Strategies using Reinforcement Learning
Sim, Kwee-Bo ; Chun, Ho-Byung ;
International Journal of Fuzzy Logic and Intelligent Systems, volume 1, issue 1, 2001, Pages 125~130
In this paper, we propose a new type of evolution strategies combined with reinforcement learning. We use the variances of fitness occurred by mutation to make the reinforcement signals which estimate and control the step length of mutation. With this proposed method, the convergence rate is improved. Also, we use cauchy distributed mutation to increase global convergence faculty. Cauchy distributed mutation is more likely to escape from a local minimum or move away from a plateau. After an outline of the history of evolution strategies, it is explained how evolution strategies can be combined with the reinforcement learning, named reinforcement evolution strategies. The performance of proposed method will be estimated by comparison with conventional evolution strategies on several test problems.