• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제8권4호
• /
• pp.306-311
• /
• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• 한국지능시스템학회논문지
• /
• 제17권6호
• /
• pp.799-803
• /
• 2007

본 논문에서는 FSVM(Putty Support Vector Machine)의 퍼지소속함수를 새롭게 제안한다. SVM의 완화변수(slack-variable)에 퍼지소속함수를 결합하는 FSVM은 주어진 데이터베이스의 특성이 반영되어 안정적으로 분류성능을 향상시킬 수 있는 퍼지소속 함수를 필요로 한다. 시계열 자료의 패턴분류 성능을 비교하기 위하여 SVM, FSVM(1), 그리고 제안하는 FSVM(2) 등의 분류모델들을 비교 실험하였다. 사용한 데이터베이스는 한국금융시장의 시계열 경제지표 지수들이다.

• Asia pacific journal of information systems
• /
• 제12권3호
• /
• pp.21-43
• /
• 2002

This paper examines internet shopping mall members' relationship quality and its antecedents variables. For this purpose, five types of membership customers' perceived variables, including convenience, product assortment, product information, shopping mall design, and service quality are proposed to affect customer satisfaction and consequently relationship quality. This study, which used data from customers of membership internet shopping malls, showed satisfactory data-fit to the proposed model and except product information hypothesis, supported all of research hypotheses. Also four types of membership customers' perceived variables(convenience, product assortment, shopping mall design, and service quality) take significant effect on customer satisfaction, and the satisfaction in turn have influence on relationship quality.

• Journal of Radiation Protection and Research
• /
• 제14권1호
• /
• pp.71-74
• /
• 1989

최소자승법을 써서 우리 학회의 연차별 회원수와 학회지 게재 논문 편수와의 상관 관계식을 구하고, 그 결과로 부터 연간 4회까지 학회지를 발간코자 할 때의 필요 회원수를 추정한 바 최소한 650여명의 회원수를 확보해야만 할 것으로 보였다.

• Smart Structures and Systems
• /
• 제26권6호
• /
• pp.797-807
• /
• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• Journal of applied mathematics & informatics
• /
• 제42권1호
• /
• pp.123-137
• /
• 2024

In this paper, Power fuzzy graphs is newly introduced by allotting fuzzy values on power graphs in such a way that the newly added edges, has the edge membership values between a closed interval which depends on vertex membership values and the length of the added edges. Power fuzzy subgraphs and total power fuzzy graphs are newly defined with properties and some special cases. It is observed that every power fuzzy graph is a fuzzy graph but the converse need not be true. Edges that are incident to vertices with the least vertex membership values are retained in the least power fuzzy subgraph. Further, the application of these concepts in real life time has been presented and discussed using power fuzzy graph model.

• 대한전자공학회논문지TE
• /
• 제39권4호
• /
• pp.363-369
• /
• 2002

본 논문은 적응성 뉴로-퍼지 인터페이스 시스템(Adaptive Neuro-Fuzzy Inference System : ANFIS)과 웨이브렛 변환 다중해상도 분해(multi-resolution Analysis : MRA)을 기반으로 한 웨이브렛 신경망을 가지고 임의의 비선형 함수 학습 근사화를 개선하는 것이다. ANFIS 구조는 벨형 퍼지 소속 함수로 구성이 되었으며, 웨이브렛 신경망은 전파 알고리즘과 역전파 신경망 알고리즘으로 구성되었다. 이 웨이브렛 구성은 단일 크기이고, ANFIS 기반 웨이브렛 신경망의 학습을 위해 역전파 알고리즘을 사용하였다. 1차원과 2차원 함수에서 웨이브렛 전달 파라미터 학습과 ANFIS의 벨형 소속 함수를 이용한 ANFIS 모델 기반 웨이브렛 신경망의 웨이브렛 기저 수 감소와 수렴 속도 성능이 기존의 알고리즘 보다 개선되었음을 확인하였다.

• 유통과학연구
• /
• 제17권9호
• /
• pp.25-33
• /
• 2019

Purpose - The purpose of the study was to seek to find out what factors having differences between paid membership customers (Costco membership) and general customers in retail industry. Since Costco operates differently from other conventional retailers, which is expected to have a substantial impact on consumers' preference of retail stores. Research design, data, and methodology - The survey conducted covered 1,000 adults in their 30s~50s living in Goyang and Gwangmyeong where Costco runs stores to determine the effects of Costco's local market-entry from consumer perspectives. 500 respondents were surveyed in each region and those working in the retail sector were excluded to ensure the objectivity of the answers. Results - Costco members in Goyang considered the price, bulk purchasing, and membership benefits as important criteria when choosing their retail store. On the other hand, as for Gwangmyeong, the non-member group's prominent characteristic was that they considered accessibility including travel distance and location and in-store amenities including food court services as important criteria for decision-making. Conclusion - Unique business model of Costco shows a statistically significant difference in terms of consumer awareness. the feature of Costco served as an critical criteria for consumers in their purchasing decision. Moreover, Bulk packaging purchases at Costco results in a strong supplementary relationship with neighborhood supermarkets.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.207-209
• /
• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제4권4호
• /
• pp.575-594
• /
• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.