• Journal of applied mathematics & informatics
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• v.37 no.1_2
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• pp.65-71
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• 2019

In this paper we give some properties related to fuzzy functions on complete residuated lattices.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.41-45
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• 2002

From the paper which it sees a strong random number generator it uses a fuzzy set from 16 method of the statistical test which is a cryptograph random number test it verifies. 16 statistical test of NIST extends in crptograph and engineering whole it is a scale which is important distinguishes the distinction incapable characterstic of the random numbers which are used. To try introduce a fuzzy set the possibility of having a more strong randomness in order to be, it strengthens the function of the random number generator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.556-561
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• 1998

This paper deals with our proposed fuzzy inference method, in which the fuzzy relation is represented by the membership functions of the antecedent and consequent parts, it is not used any fuzzy composition. The strong point of this method is that the membership function of an inferred conclusion has a simple shape and thus its meaning can be interpreted easily. Firstly, the proposed method is explained, and then it is applied to fuzzy modeling of distributed data.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.968-970
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• 2003

Fuzzy Controller is a system that displays a person's thoughts using membership function and IF-THEN rules. With the help of specialists' knowledge, rule bases can be explained in easy language. Furthermore Fuzzy Controller has strong resistance against turbulence. Its performance is especially prominent when targets cannot be measured in mathematic methods because the fuzzy controller can measure the output using only the relations between the input and output. But Fuzzy System has a problem that is calculation speed. I suggest you a theory to solve it. I applied a theory to inverted pendulum. Because it is represent of nonlinear system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.357-368
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• 2014

Since its birth in 1993, fuzzy time series have seen different classes of models designed and applied, such as fuzzy logic relation and rule-based models. These models have both advantages and disadvantages. The major drawbacks with these two classes of models are the difficulties encountered in identification and analysis of the model. Therefore, there is a strong need to explore new alternatives and this is the objective of this paper. By transforming a fuzzy number to a real number via integrating the inverse of the membership function, new autoregressive models can be developed to fit the observation values of a fuzzy time series. With the new models, the issues of model identification and parameter estimation can be addressed; and trends, seasonalities and multivariate fuzzy time series could also be modeled with ease. In addition, asymptotic behaviors of fuzzy time series can be inspected by means of characteristic equations.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.965-967
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• 2003

Fuzzy Controller is a system that displays a person's thoughts using membership function and IF-THEN rules. With the help of specialists' knowledge, rule bases can be explained in easy language. Furthermore Fuzzy Controller has strong resistance against turbulence. Its performance is especially prominent when targets cannot be measured in mathematic methods because the fuzzy controller can measure the output using only the relations between the input and output. With the increasing influence of multimedia on our daily lives, vision plays bigger role both in industries and personal lives. Like wise vision is being used in many areas such as detecting and identifying objects. It is difficult to detect and control targets because there is a delay in the calculating when using vision in detecting and controlling objects in large quantity. In this paper we showed how to use fuzzy controller in minimizing the calculation process, controlling target objects and moving view window instead of applying input variation through vision. Ball beam, which has strong nonlinear, was used as the target object and DSP320C6711 IDK by TI(Texas Instruments) company was for the benefit of speedy calculation and vision data operation.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.137-147
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• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.29-35
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• 2012

This paper introduces an adaptive control method of strong mutation rate and probability for queen-bee genetic algorithms. Although the queen-bee genetic algorithms have shown good performances, it had a critical problem that the strong mutation rate and probability should be selected by a trial and error method empirically. In order to solve this problem, we employed the measure of convergence and used it as a control parameter of those. Experimental results with four function optimization problems showed that our method was similar to or sometimes superior to the best result of empirical selections. This indicates that our method is very useful to practical optimization problems because it does not need time consuming trials.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.49-55
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• 2002

This paper proposes speaker recognition algorithm which includes both the pitch parameter and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in odor to include time variation width for non-linear utterance time.