• Journal of Electrical Engineering and Technology
• /
• v.5 no.4
• /
• pp.653-665
• /
• 2010

In this study, we introduce a neurofuzzy approach to the design of fuzzy controllers. The development process exploits key technologies of Computational Intelligence (CI), namely, genetic algorithms (GA) and neurofuzzy networks. The crux of the design methodology deals with the selection and determination of optimal values of the scaling factors of fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out. Next, we form a nonlinear mapping for the scaling factors, which are realized by GA-based neurofuzzy networks by using a fuzzy set or fuzzy relation. The proposed approach is applied to control nonlinear systems like the inverted pendulum. Results of comprehensive numerical studies are presented through a detailed comparative analysis.

• Proceedings of the Korean Society for Rock Mechanics Conference
• /
• 2004.10a
• /
• pp.171-180
• /
• 2004

Underground mining causes surface subsidence long after the mining operation had been ceased. Surface subsidence can be in the form of saucer-shaped depression or collapsed chimneys or sinkholes. Sinkhole formations are predominant over shallow-depth room and pillar mines having weak overburden strata. In this study, occurrences of sinkholes due to mining activity are assessed based on local geological conditions and mining parameters using fuzzy reasoning techniques. All input and output parameters are represented with linguistic hedges. Numerous fuzzy rules are developed to relate sinkhole occurrences with input parameters using fuzzy relational matrix. Based on the combined fuzzy rules, possibility of sinkhole occurrences can be ascertained once the geological and mining parameters of any area are known.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.720-723
• /
• 1997

The characteristics of ball and beam system using fuzzy inference technique can be described by fuzzy modeling. Therefore, this paper introduces a technique for fuzzy structure identification of nonlinear Input-output relation- ship using an adaptive fuzzy inference system. And the simulation result using adaptive fuzzy inference technique shows its effectiveness for fuzzy structure identification of nonlinear system.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.717-719
• /
• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller and propose the tuning method for them. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. An approximate transfer function of a fuzzy controller is derived from the comparison a fuzzy controller with the conventional PID controller. We analyze the effects of scaling factor using this approximate transfer function and propose a fuzzy tuning method based on that of Maeda et al[4].

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.1-4
• /
• 2002

There have been several tipical methods being used to measure the fuzziness (entropy) of fuzzy sets. Pedrycz is the original motivation of this paper. This paper studies the entropy variation on the fuzzy numbers with arithmetic operations(addition, subtraction, multiplication) and the relationship between entropy and information energy. It is shown that through the arithmetic operations, the entropy of the resultant fuzzy number has the arithmetic relation with the entropy of each original fuzzy number. Moreover, the information energy variation on the fuzzy numbers is also discussed. The results generalize earlier results of Pedrycz [FSS 64(1994) 21-30] and Wang and Chiu [FSS 103(1999) 443-455].

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.240-245
• /
• 1998

Fuzzy information retrieval which uses the concept of fuzzy relation is able to retrieve documents in the way based on not morphology but semantics, dissimilar to traditional information retrieval theories. Fuzzy information retrieval logically consists of three sets : the set of documents, the set of terms and the set of queries. It maintains a fuzzy relational matrix which describes the relationship between documents and terms and creates a thesaurus with fuzzy relational product. It also provides the user with documents which are relevant to his query. However, there are some problems on building a thesaurus with fuzzy relational product such that it has big time complexity and it uses fuzzy values to be processed with flating-point. Actually, fuzzy values have to be expressed and processed with floating-point. However, floating-point operations have complex logics and make the system be slow. If it is possible to exchange fuzzy values with binary values, we could expect sp eding up building the thesaurus. In addition, binary value expressions require just a bit of memory space, but floating -point expression needs couple of bytes. In this study, we suggest a new method of building a thesaurus, which accelerates the operation of the system by pre-applying an ${\alpha}$-cut. The experiments show the improvement of performance and reliability of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.141-144
• /
• 2007

일반적으로 의사결정의 대상이 되는 현실 시스템은 매우 가변적 (variable)이며 때로는 많은 불확실성(uncertainty)이 포함된 상황에 놓일 수 있다. 이러한 문제의 처리를 위한 통계적 방법으로 유의수준이나 확신도, 민감도 분석 등이 사용된다. 본 논문에서는 먼저 근접관계 행렬에서 근접도를 구하는 방법으로 상대적 해밍거리와 max-min방법을 이용한 다음, 다중임계치를 사용하여 최적구간분할을 하는 방법을 제안한다. 결과적으로 max-min방법을 이용하여 다중임계치을 적용한 근접관계의 분류가 상대적 해밍거리로 근접도를 구하여 다중임계치를 구하는 방법보다 계산과정이 더 간단하고 명확하며 분할과정을 줄일 수 있고 최적의 의사결정에 효율적이라는 것을 알 수 있다.

• Honam Mathematical Journal
• /
• v.34 no.1
• /
• pp.77-84
• /
• 2012

In this paper, we define the weakly commuting mapping and prove the fixed point theorem for weakly commuting mappings under some conditions on intuitionistic fuzzy metric spaces.

• Honam Mathematical Journal
• /
• v.32 no.4
• /
• pp.663-673
• /
• 2010

In this paper, we will establish common fixed point for compatible mappings of type(${\alpha}$) for four self mappings defined on intuitionistic fuzzy metric space with implicit relations.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.2
• /
• pp.3-12
• /
• 1995

A controller utilizing fuzzy logic is developed to control the speed of a motor in a washing machine by choosing an appropriate phase. Due to the hardship imposed on obtaining a result from a relation established for inputs, present speed and present rate of speed, and ouput, a phase, of the system that can be tested against an experimental result, it is impossible to apply a genetic algorithm to fine-tune the fuzzy logic controller. To avoid this difficulty, a proper assumption that the parameters of an if-part of a primary fuzzy logic controller have a functional relationship with an error between computed values and experimental ones in made. Setting up of a fuzzy relationship between the parameters and the errors is then achieved through experimentally obtained data. Genetic Algorithm is then applied to this secondary fuzzy logic controller to verify the fuzzy logic. In the verification process, the primary fuzzy logic controller is used in obtaining experimental results. In this way the kind of difficulty in obtaining enough experimental values used to verify the fuzzy logic with genetic algorithm is gotten around. Selection of the parameters that would produce the least error when using the secondary fuzzy logic controller is done with applying genetic algorithm to the then-part of the controller. In doing so the optimal values for the parameters of the if-part of the primary fuzzy logic controller are assumed to be contained. The experimental result presented in the paper validates the assumption.