• 한국건설관리학회논문집
• /
• 제5권5호
• /
• pp.143-150
• /
• 2004

본 연구는 다기준의사결정문제인 건설 프로젝트의 공법선정문제에 있어서 퍼지계층분석법 및 그 결과 생성되는 각 공법별 퍼지 점수의 상대평가를 위해 퍼지 선호도 함수를 적용하여 상대평가를 하고자 하였다. 지금까지의 건설 공법 선정에 대한 퍼지계층분석법에 대한 연구는 대부분 최종적인 공법선정을 위해서 각 공법별로 도출된 퍼지 점수의 순위결정기법으로 절대평가를 수행하였다. 그러나 이러한 기법은 비교 대상공법에 대한 일관적인 순위결과를 산출해 내지 못하므로 결과적으로 공법선정과정의 전반적인 타당성을 저해하는 문제점을 지니고 있었다. 따라서 본 연구에서는 건설 분야의 MCDM(Multiple Criteria Decision Making)에 관한 기존의 연구들을 바탕으로 순위 결정기법에 R.P.R(Relative Preference Ratio)기법을 도입하여 각 공법에 대한 퍼지 점수를 상대 평가함으로써 체계적이고 효율적인 건설 공법선정기법을 제시하였고, 이를 창호공법의 선정문제에 적용하여 그 타당성을 살펴보았다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제13권3호
• /
• pp.171-177
• /
• 2013

This paper presents a fuzzy set method to enforce complementarity constraints (CCs) in a nonlinear interior point method (NIPM)-based optimization. NIPM is a Newton-type approach to nonlinear programming problems, but it adopts log-barrier functions to deal with the obstacle of managing inequality constraints. The fuzzy-enforcement method has been implemented for CCs, which can be incorporated in optimization problems for real-world applications. In this paper, numerical simulations that apply this method to power system optimal power flow problems are included.

• 융합신호처리학회 학술대회논문집
• /
• 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
• /
• pp.133-136
• /
• 2001

In this paper, we propose a calculation method for fuzzy control based on quantized $\alpha$ -cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference result is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzificaion by gravity center method by PWM are also presented.

• 산업공학
• /
• 제9권1호
• /
• pp.53-62
• /
• 1996

The Delphi method is widely used for long and middle range forecasting in management science. It is a method by which the subjective data of experts are made to converge using statistical analysis. The Fuzzy Delphi Method(F.D.M.), anew application of the Delphi method using Triangular Fuzzy Numbers(T.F.N.), can help to predict the uncertainty, synthesize the opinion and calculation of those assumed dissemblance index and fuzzy distance. Furthermore, the programming of the F.D.M. process to feed paper and data back to experts can make them more accurately predict the various information.

• 한국정보통신학회논문지
• /
• 제3권2호
• /
• pp.363-371
• /
• 1999

본 논문에서는 유전자 알고리즘을 이용한 최적의 퍼지 제어기 설계에 대한 방식을 제안한다. 제안하는 방식은 최적화 문제에 매우 효과적인 유전자 알고리즘을 이용하여 퍼지 제어기의 퍼지규칙, 입ㆍ출력 스케일링 펙터를 결정하는 방식이다. 서보 시스템에 적합한 퍼지 규칙은 퍼지 제어기의 성능지표인 적합도 함수를 사용한다. 제안된 제어 방식의 유용성을 확인하기 위하여 단일 링크 매니퓰레이터를 제어 대상으로 시뮬레이션 및 실험을 하여 일반적인 퍼지 제어 방식과 제어 성능 및 특성을 비교 검토한다.

• 한국안전학회지
• /
• 제20권1호
• /
• pp.126-132
• /
• 2005

The purpose of this study is to propose a method to evaluate task complexity using CIFs(Complexity Influencing Factors). We developed a method that CIFs can be used in the evaluation of task complexity using fuzzy linguistic approach. That is, a fuzzy linguistic multi-criteria method to assess task complexity in a specific task situation was proposed. The CIFs luting was assessed in linguistic terms, which are described by fuzzy numbers with triangular and trapezoidal membership function. A fuzzy weighted average algorithm, based on the extension principle, was employed to aggregate these fuzzy numbers. Finally, the method was validated by experimental approach. In the result, it was validated that TCIM(Tink Complexity Index Method) is an efficient method to evaluate task complexity because the correlation coefficient between task performance time and TCI(Task Complexity Index) was 0.699.

• 대한전기학회논문지:전력기술부문A
• /
• 제49권12호
• /
• pp.589-594
• /
• 2000

The fuzzy controllers have been applied to the power system stabilizer due to its excellent properties on the nonlinear systems. But the design process of fuzzy controller requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This process is time consuming task. This paper presents an parameters tuning method of the fuzzy power system stabilizer using the genetic algorithm and simulated annealing(SA). The proposed method searches the local minimum point using the simulated annealing algorithm. The proposed method is applied to the one-machine infinite-bus of a power system. Through the comparative simulation with conventional stabilizer and fuzzy stabilizer tuned by genetic algorithm under various operating conditions and system parameters, the robustness of fuzzy stabilizer tuned by proposed method with respect to the nonlinear power system is verified.

• Journal of applied mathematics & informatics
• /
• 제26권5_6호
• /
• pp.861-876
• /
• 2008

This paper concerns a new method called Fuzzy Supervised Method for error matrix, the method has developed based on Adoptive Neuro- Fuzzy Inference Systems(ANFIS). For the performance point of view initially the new method tested with trial data and then this paper applies the proposed method with real world problems. So that this paper generated 1000 random error matrices in programming language [R] and then it tests the new proposed method for the error matrices. The results of Fuzzy Supervised Method given in terms of Kappa Index and Congalton Accuracy Indexes, and performance of Fuzzy Supervised Method has evaluated by using Pearson's test.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권4호
• /
• pp.225-237
• /
• 2016

In conventional transportation problem (TP), all the parameters are always certain. But, many of the real life situations in industry or organization, the parameters (supply, demand and cost) of the TP are not precise which are imprecise in nature in different factors like the market condition, variations in rates of diesel, traffic jams, weather in hilly areas, capacity of men and machine, long power cut, labourer's over time work, unexpected failures in machine, seasonal changes and many more. To counter these problems, depending on the nature of the parameters, the TP is classified into two categories namely type-2 and type-4 fuzzy transportation problems (FTPs) under uncertain environment and formulates the problem and utilizes the trapezoidal fuzzy number (TrFN) to solve the TP. The existing ranking procedure of Liou and Wang (1992) is used to transform the type-2 and type-4 FTPs into a crisp one so that the conventional method may be applied to solve the TP. Moreover, the solution procedure differs from TP to type-2 and type-4 FTPs in allocation step only. Therefore a simple and efficient method denoted by PSK (P. Senthil Kumar) method is proposed to obtain an optimal solution in terms of TrFNs. From this fuzzy solution, the decision maker (DM) can decide the level of acceptance for the transportation cost or profit. Thus, the major applications of fuzzy set theory are widely used in areas such as inventory control, communication network, aggregate planning, employment scheduling, and personnel assignment and so on.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제49권8호
• /
• pp.423-431
• /
• 2000

This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.