fuzzy regression model
Multiple Fuzzy Regression Model on Two Wheelers’ Mileage with Several independent Factors
... Abstract. Regression is one of the important factors of statistical ...statistical regression are bounded by the quantitative ...estimation. Fuzzy logic is one of the best ways to deal with such ...a ...
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Fuzzy Regression Model and Its Application: A Review
... situation fuzzy regression model is appropriate and gives better ...and fuzzy then we have to fit the Fuzzy regression ...conventional regression is appropriate for only ...
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Fuzzy Regression Model Based on Fuzzy Distance Measure
... existed fuzzy regression methods have some special requirements for the object of study, such as assuming the observed values as symmetric tri- angular fuzzy numbers or imposing a non-negative ...
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An adaptive fuzzy regression model for the prediction of dichotomous response variables
... possibilistic fuzzy regression technique is however applicable to linear functions only ...possibilistic fuzzy linear regression model which is then solved by using linear programming ...
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Regression Analysis of a Kind of Trapezoidal Fuzzy Numbers Based on a Shape Preserving Operator
... specific model al- gorithms for FIFCFO model (fuzzy input-fuzzy coefficient-fuzzy output mod- el) and introduce three advantages of fit criteria, Error Index, Similarity Measure and ...
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A support vector based interval type 2 fuzzy system
... new fuzzy regression model that is supported by support vector regression is ...2 fuzzy systems are able to tackle applications that have significant ...type-2 fuzzy systems are ...
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[14] . The T-S fuzzy model consists of
... T-S fuzzy model to deal with imprecise ...the fuzzy sets (i.e., to find fuzzy rules or structure of data) in the antecedents when the response x is fuzzy ...T-S fuzzy ...
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Statistical Analysis of Fuzzy Linear Regression Model Based on Centroid Method
... of fuzzy regression: minimum fuzzy criteria, least squares fitting criteria and interval regression analysis ...between fuzzy regression and conventional regression is ...
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A Variable Structural Control for a Flexible Plate
... Linear regression models are used to model the functional relationship between the response and the predictors ...The fuzzy regression model is a practical alternative if the linear ...
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Robust Regression Analysis with LR Type Fuzzy Input Variables and Fuzzy Output Variable
... robust fuzzy regression model based on a hyperelliptic ...generalized fuzzy weighted least squares method for an outlier condition, making weighted with degree of membership and lean on an ...
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BAYESIAN SEMIPARAMETRIC REGRESSION WITH FUZZY SETS
... Abstract: In this paper, Bayesian approach to semiparametric regression is described using fuzzy sets and membership functions. The membership functions are interpreted as likelihood functions for the ...
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A combination of genetic algorithm based fuzzy c means with a convex hull based regression for real time fuzzy switching regression analysis: application to industrial intelligent data analysis
... we have demonstrated that the convex hull-based fuzzy regression approach performs efficiently for real-time data processing for fuzzy switching regression problems; this method could re[r] ...
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The Establishment of Decision Model Based on Fuzzy Regression and the Application of Chemical Solid Adsorption Quantity
... Regression analysis is a commonly used statistical analysis model. It can conjecture a value of certain random through a variable or a set of variables. This method can help us to make analysis and judgment ...
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Failure Prediction of Cross-Ply Laminated Double-Serial Mechanically Fastened Composites using Fuzzy Expert System
... Sen et al. [12] investigated the improvement of an artificial neural network (ANN) method for the prediction of bearing strength of two serial pinned/ bolted E-glass reinforced epoxy composite joints. Comparisons of ANN ...
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Fuzzy random regression to improve coefficient estimation for Malaysian agricultural industry
... of fuzzy random variables that would play an essential role in the constructive definition of their integrals, which will be especially valuable to perform practical computations and to develop further results ...
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A technique of fuzzy c mean in multiple linear regression model toward paddy yield
... century. Regression analysis has become one of the standard tools in data ...Multiple regression is a flexible method of data analysis that may be appropriate whenever a quantitative variable is to be ...
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An Efficient Regression Based Demand Forecasting Model including temperature with Fuzzy Ideology for Assam
... the fuzzy set based classifier ...the fuzzy inference system through fuzzification block. The fuzzy inference block is the heart of the system as it processes the input data and gives output as the ...
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Error Estimation Using Fuzzy Linear Regression Analysis
... Abstract. In this paper an attempt is made to reduce the error of non-fuzzy data using fuzzy linear regression. A numerical example has been analyzed. It is concluded from the example that the normal ...
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Comparative Predictive Analysis of Material Removal Rate (MRR) of Wire Electrical Discharge Machining (WEDM) of High Carbon High Chromium Die Steel
... as fuzzy logic (FL) Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) are used as unconventional tools for modelling of nonlinear data mining ...FL model works with a ...
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Intellectual capital and its determinants in Italian listed companies
... Valuation Model” of Pantzalis and Park (2009) provides a way to relate human capital (measured as the ratio of total firm employees to total industry employees) to market ...the model does not consider two ...
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