Titlebook: Optimal Models and Methods with Fuzzy Quantities; Bing-Yuan Cao Book 20101st edition Springer-Verlag Berlin Heidelberg 2010 Analysis.Regre

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Regression and Self-regression Models with Fuzzy Variables,90a], and, again in 1992, a linearizable non-linear regression model with .-fuzzy variables [Cao95c] was developed. The application appears vastly extensive because of much wider information in models..1) Make use of a fuzzy distance, follow the classic regression analytical method with a beeline( o

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Fuzzy Geometric Programming,th a bottom, but without a cover, whose bottom and two sides are made from . of a special flexible material with negligible cost. The material for the other two sides cost more than A yuan/. (yuan means RMB), and transportation of the case costs about . yuan. What is the cost at least to ship one ca

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Interval and Fuzzy Differential Equations,ation. At the same time, we research Solow economical increase model, and Duoma debt models influencing very greatly in economics, by applying a fuzzy set-value mapping method to extension of the differential equation.

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Book 20101st editionession Models with Fuzzy Variables, Fuzzy Input/output Model, Fuzzy Cluster Analysis and Fuzzy Recognition,  Fuzzy Linear Programming, Fuzzy Geometric Programming, Fuzzy Relative Equation and Its Optimizing, Interval and Fuzzy Differential Equations and Interval and Fuzzy Functional and Their Variat

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Regression and Self-regression Models with Fuzzy Variables,terval estimation, a kind of analytical methods become much useful..This chapter introduces T -fuzzy variables, (·, .) fuzzy variables and flat (or trapezoidal) fuzzy variables into regression models, and builds more practical kinds of way to the model determination. Meanwhile, their application is discussed.