• 제목/요약/키워드: fuzzy regression model

검색결과 152건 처리시간 0.03초

FUZZY REGRESSION TOWARDS A GENERAL INSURANCE APPLICATION

  • Kim, Joseph H.T.;Kim, Joocheol
    • Journal of applied mathematics & informatics
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    • 제32권3_4호
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    • pp.343-357
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    • 2014
  • In many non-life insurance applications past data are given in a form known as the run-off triangle. Smoothing such data using parametric crisp regression models has long served as the basis of estimating future claim amounts and the reserves set aside to protect the insurer from future losses. In this article a fuzzy counterpart of the Hoerl curve, a well-known claim reserving regression model, is proposed to analyze the past claim data and to determine the reserves. The fuzzy Hoerl curve is more flexible and general than the one considered in the previous fuzzy literature in that it includes a categorical variable with multiple explanatory variables, which requires the development of the fuzzy analysis of covariance, or fuzzy ANCOVA. Using an actual insurance run-off claim data we show that the suggested fuzzy Hoerl curve based on the fuzzy ANCOVA gives reasonable claim reserves without stringent assumptions needed for the traditional regression approach in claim reserving.

퍼지 회귀모델을 이용한 연삭가공용 데이타 베이스의 설계와 활용(실가공 데이타베이스에 관하여) (Architecture and Implementation of Database on the Cylindrical Grinding Utilizing the Fuzzy Regression Model)

  • 김건회;도기일랑;이재경;송지복
    • 한국정밀공학회지
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    • 제11권1호
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    • pp.219-229
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    • 1994
  • This paper describes an expert system on the cylindrical grinding operations in order to establish the optimum grinding conditions, which satisfy the maximum removal rates, considering the several constraints of grinding power, workpiece burn, chatter vibration and surface roughness. Specialized knowledge of the grinding operations are acquired from the actual operation database. Coefficientis in the experimental equations are obtaines through the fuzzy regression model based on the fuzzy set theory, and are stored in the actual operation database. The developed system is capable of determining the optimum grinding conditions taking into account some problems, and practical examples of implementaion are described.

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Kernel-Based Fuzzy Regression Machine For Predicting Turbulent Flows

  • 홍덕헌;황창하
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2004년도 춘계학술대회
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    • pp.91-101
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    • 2004
  • The turbulent flow is of fundamental interest because the conservation equations for thermodynamics, mass and momentum are linked together. This turbulent flow consists of some coherent time- and space-organized vortical structures. Research has already shown that some dynamic systems and experimental models still cannot provide a good nonlinear analysis of turbulent time series. In the real turbulent flow, very complicated nonlinear behaviors, which are affected by many vague factors are present. In this paper, a kernel-based machine for fuzzy nonlinear regression analysis is proposed to predict the nonlinear time series of turbulent flows. In order to show the practicality and usefulness of this model, we present an example of predicting the near-wall turbulence time series as a verifiable model and compare with fuzzy piecewise regression. The results of practical applications show that the proposed method is appropriate and appears to be useful in nonlinear analysis and in fuzzy environments to predict the turbulence time series.

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Extended Fuzzy DEA

  • Guo, Peijun;Tanaka, Hideo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.517-521
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    • 1998
  • DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

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회귀모형을 이용한 한국프로농구 승부결과 분석 (Analysis of the outcome for the Korean Pro-Basketball games using Regression models)

  • 장효진;곽현;최승회
    • 한국지능시스템학회논문지
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    • 제25권5호
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    • pp.489-494
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    • 2015
  • 본 연구의 목적은 프로농구 경기의 승부 결과를 회귀모형을 이용하여 분석하는 것이다. 이를 위해 본 연구에서는 전통적인 회귀분석 방법과 문자적인 변수를 사용하는 퍼지회귀모형을 사용하였다. 승부의 결과를 두 팀 간의 점수차로 표현하여 분석한 일반회귀분석 방법에서는 두 팀의 점수차에 영향을 미치는 변수를 찾아 승부의 결과에 대한 회귀모형을 제시하였다. 그리고 두 팀의 승부 결과를 "대승, 승리, 신승, 석패, 패배 그리고 대패"와 같이 문자적으로 표현한 퍼지회귀모형에서는 각 팀의 경기력과 조직력을 퍼지수로 표현하여 각 팀의 경기력과 조직력이 승부의 결과에 미치는 영향을 분석하였다. 본 연구는 한국프로농구연맹(KBL, Korea Basketball League)에서 제공하는 2013~2014시즌의 자료와 프로농구의 결과를 분석하는 칼럼들을 이용하여 분석하였다.

A SOFT-SENSING MODEL FOR FEEDWATER FLOW RATE USING FUZZY SUPPORT VECTOR REGRESSION

  • Na, Man-Gyun;Yang, Heon-Young;Lim, Dong-Hyuk
    • Nuclear Engineering and Technology
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    • 제40권1호
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    • pp.69-76
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    • 2008
  • Most pressurized water reactors use Venturi flow meters to measure the feedwater flow rate. However, fouling phenomena, which allow corrosion products to accumulate and increase the differential pressure across the Venturi flow meter, can result in an overestimation of the flow rate. In this study, a soft-sensing model based on fuzzy support vector regression was developed to enable accurate on-line prediction of the feedwater flow rate. The available data was divided into two groups by fuzzy c means clustering in order to reduce the training time. The data for training the soft-sensing model was selected from each data group with the aid of a subtractive clustering scheme because informative data increases the learning effect. The proposed soft-sensing model was confirmed with the real plant data of Yonggwang Nuclear Power Plant Unit 3. The root mean square error and relative maximum error of the model were quite small. Hence, this model can be used to validate and monitor existing hardware feedwater flow meters.

On Chaotic Behavior of Fuzzy Inferdence Rule Based Nonlinear Functions

  • Ikoma, Norikazu
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.861-864
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    • 1993
  • This research provides the results of a trial to generate the chaos by using nonlinear function constructed by fuzzy inference rules. The chaos generation function or chaotic behavior can be obtained by using Takagi-Sugeno fuzzy model with some constraint of the relationship of its parameters. Two examples are shown in this research. The first is simple example that construct of logistic image by fuzzy model. The second is more complicated one that provide the chaotic time series by non-linear autoregression based on fuzzy model. Simulated results are shown in these examples.

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Fuzzy 회귀분석기법을 이용한 평창강 유역의 설계홍수량 산정 (Design Flood Estimation for Pyeongchang River Basin Using Fuzzy Regression Method)

  • 이재응;김승주;이태근;지정원
    • 한국수자원학회논문집
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    • 제45권10호
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    • pp.1023-1034
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    • 2012
  • 선형회귀분석기법은 오랫동안 수공학분야뿐만 아니라 경제학, 통계학 등 여러 분야에서 널리 이용되어 왔다. Fuzzy 회귀분석기법은 자료의 불확실성이 높을 때 이를 정량화하여 회귀분석 모형에 반영할 수 있다. 본 연구에서는 평창강 유역의 임의 지점에서 설계 홍수량을 산정하기 위해 fuzzy 회귀분석모형을 개발하였다. 평창강 유역과 같은 산지하천 유역은 관측소의 부재로 홍수유출해석에 필요한 자료의 습득이 어려운 경우가 많이 있다. 본 연구에서는 지리정보시스템을 이용하여 유역특성인자를 공간적으로 분석하고, 그 결과를 바탕으로 미계측 산지유역에서 설계홍수량을 산정할 수 있는 기법을 검토하였다. Fuzzy 회귀분석기법을 산지하천 유역의 특성을 가지고 있으며 IHP 시험유역 운영을 통하여 비교적 강우와 유량자료가 잘 수집되어 있는 평창강 유역에 적용하였다. 평창강 유역에 대해서 유역특성인자를 이용하여 fuzzy 설계홍수량 산정식을 개발하였고, 유역의 본류를 따라 위치하고 있는 9개의 지점에서 산정된 빈도홍수량과 비교하여 개발된 산정식의 적합성을 검토하였다. Fuzzy 회귀분석을 사용하여 지역회귀분석을 수행한다면 자료 관측에서 발생하는 빈도홍수량의 불확실성을 정량화하고, 불확실성의 전파를 파악할 수 있다.

Trend in Fuzzy Regression Model

  • 최승회;김해경;정은경
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.73-77
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    • 2004
  • 종속변수와 독립변수 사이의 통계적인 관계를 설명하기 위해 사용되는 회귀모형을 분석하는 방법을 회귀분석이라 한다. 독립변수와 종속변수가 퍼지수인 퍼지회귀모형을 추정하기 위해 최소전대편차추정량을 제시하고. 예제를 이용하여 퍼지최소절대편차회귀모형과 퍼지최소자 승회귀모형의 효율성을 평가한다.

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Neuro-fuzzy optimisation to model the phenomenon of failure by punching of a slab-column connection without shear reinforcement

  • Hafidi, Mariam;Kharchi, Fattoum;Lefkir, Abdelouhab
    • Structural Engineering and Mechanics
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    • 제47권5호
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    • pp.679-700
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    • 2013
  • Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more user-friendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.