• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.75-81
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• 2008

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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.60-67
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for a synchronous generator excitation and SVC system. A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the most flexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method. The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.115-120
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• 2006

This article propose a new idea of developing a hybrid scheme to achieve faster INS alignment with higher accuracy using a novel procedure to estimate the initial attitude angles that combines a Kalman filter and Adaptive Neuro-Fuzzy Inference System architecture. A tactical grade inertial measurement unit was applied to verify the performance of proposed scheme in this study. The preliminary results indicated the outstanding improvements in both time consumption for fine alignment process and accuracy of estimated attitude angles, especially in heading angles. In general, the improvement in terms of time consumption and the accuracy of estimated attitude estimated accuracy reached 80% and 70% respectively during alignment process after compensating the attitude angles estimated by an extended Kalman filter with 15 states using proposed approach. It is worth mentioned that the proposed approach can be implemented in general real time navigation applications.

• Structural Engineering and Mechanics
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• v.26 no.5
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• pp.517-544
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• 2007

This study shows a fuzzy tuning scheme to fuzzy sliding mode controller (FSMC) for seismic isolation of earthquake-excited structures. The sliding surface can rotate in the phase plane in such a direction that the seismic isolation can be improved. Since ideal sliding mode control requires very fast switch on the input, which can not be provided by real actuators, some modifications to the conventional sliding-mode controller have been proposed based on fuzzy logic. A superior control performance has been obtained with FSMC to deal with problems of uncertainty, imprecision and time delay. Furthermore, using the fuzzy moving sliding surface, the excellent system response is obtained if comparing with the conventional sliding mode controller (SMC), as well as reducing chattering effect. For simulation validation of the proposed seismic response control, 16-floor tall building has been considered. Simulations for six different seismic events, Elcentro (1940), Hyogoken (1995), Northridge (1994), Takochi-oki (1968), the east-west acceleration component of D$\ddot{u}$zce and Bolu records of 1999 D$\ddot{u}$zce-Bolu earthquake in Turkey, have been performed for assessing the effectiveness of the proposed control approach. Then, the simulations have been presented with figures and tables. As a result, the performance of the proposed controller has been quite remarkable, compared with that of conventional SMC.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.59-62
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture, is systematically conducted for the automatic controlled system. In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA; Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES; Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultiviation results.

• Proceedings of the KIEE Conference
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• summer
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• pp.292-294
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• 2004

In this paper, we design the GA-fuzzy precompensator of a Power System Stabilizer for Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for TCSC-PSS. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing TCSC-PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership Auction and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.221-235
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• 2015

Risk assessment is an important phase of risk management. It is the stage in which risk is measured thoroughly to achieve effective management. Some factors such as probability and impact of risk have been used in the literature related to construction projects. Because in high-rise projects safety issues are paramount, this study has tried to develop a quantifying technique that takes into account three factors: probability, impact and Safety Performance Index (SPI) where the SPI is defined as the capability of an appropriate response to reduce or limit the effect of an event after its occurrence with regard to safety pertaining to a project. Regarding risk-related literatures which cover an uncertain subject, the proposed method developed in this research is based on a fuzzy logic approach. This approach entails a questionnaire in which the subjectivity and vagueness of responses is dealt with by using triangular fuzzy numbers instead of linguistic terms. This method returns a Risk Critical Point (RCP) on a zoning chart that places risks under categories: critical, critical-probability, critical-impact, and non-critical. The high-rise project in the execution phase has been taken as a case study to confirm the applicability of the proposed method. The monitoring results showed that the RCP method has the inherent ability to be extended to subsequent applications in the phases of risk response and control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.70-77
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• 2002

This paper describes a design driven approach to drive intelligent test plan generation based on adaptive use case (3,5). Its foundation is an object-oriented software design approach which partitions design schema into design architecture of functional components called “design component”. A use case software development methodology of adaptive use case approach developed in I.I .T is employed which preserves this unit architecture on through to the actual code structure. Based on the partition design schema produced during the design phase of this methodology, a test plan is generated which includes a set of component and scenario based test. A software metric is introduced which produces an ordering of this set to enhance productivity and both promote and capitalize on test case reusability, This paper contains an application that illustrates the proposed approach.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.148-153
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• 2007

This paper deals with implementing a steganography based multi-modal biometric system. For this purpose, we construct a multi-biometrics system based on the face and iris recognition. Here, the feature vector of iris pattern is hidden in the face image. The recognition system is designed by the fuzzy-based Linear Discriminant Analysis(LDA), which is an expanded approach of the LDA method combined by the theory of fuzzy sets. Furthermore, we present a watermarking method that can embed iris information into face images. Finally, we show the advantages of the proposed watermarking scheme by computing the ROC curves and make some comparisons recognition rates of watermarked face images with those of original ones. From various experiments, we found that our proposed scheme could be used for establishing efficient and secure multi-modal biometric systems.