This paper presents a mathematical model for dynamic decision making with an objective function induced from fuzzy preferences. The fuzzy preference is related to decision making in artificial intelligence, and this paper models human behavior based on his fuzzy preferences. A reasonable criterion based on fuzzy preferences is formulated for the dynamic decision making, and an optimality equati...

Let R be a commutative ring with non-zero identity and let M be a non-zero unitary R-module. The concept of fuzzy coprimary submodule as a dual notion of fuzzy primary one will be introduced and some of its properties will be studied. Among other things, the behavior of this concept with respect to fuzzy localization formation and fuzzy quotient will be examined.

An inference engine using fuzzy logic is proposed for the analysis of Likert-type questionnaire. This method was used to understand and incorporate the imprecision of items in a questionnaire so that a single score that encompassed the different scales of the questionnaire could be created. A parent-rated questionnaire called the Parent Checklist of Peer Relationships (PCPR) was used as an exam...

In this article, the aim is define fuzzy agents with dynamic personality for the simulation of human behavior. Fuzzy sets are defined for personality traits and facets and the concise representation of personality knowledge is processed in fuzzy logic. This work is based on the personality knowledge as distilled from psychology [Ören and GhasemAghaee 2003a].

In this work, we present the induction of a fuzzy model that represents the behavior of a partial known function. We extend the approach of classical induction of a classifier by building a decision tree, and its generalization for regression problems by CART, to build a fuzzy model. It is defined by a collection of fuzzy regions fixed in the input domain of the function. To obtain fuzzy region...

Qualitative modeling of technical processes may be accomplished by dynamic fuzzy systems. A new inference method with interpolating rules is proposed as an essential basis for the analysis of this class of systems. Using this approach, the system output is dependent on both an interpolating rule derived from the fuzzy input and the fuzzy input itself. A simple example shows the typical behavior...

Intuitionistic fuzzy relations on finite universes can be represent by intuitionistic fuzzy matrices and the limiting behavior of the power matrices depends on the algebraic operation employed on the matrices. In this paper, the power of intuitionistic fuzzy matrices with maxarithmetic mean-minarithmetic mean operation have been studied. Here it is shown that the power of intuitionistic fuzzy m...

Fuzzy gain-scheduling is a special form of model-based fuzzy control that uses linguistic rules and fuzzy reasoning to determine the controller parameter transition policy for a dynamic plant subject to large changes in its operating state. Issues of stability and overall dynamic behavior are resolved using conventional modern control techniques. The design of a fuzzy gain-scheduling controller...

The uncertain nonlinear systems can bemodeled with fuzzy equations by incorporating the fuzzy set theory. In this paper, the fuzzy equations are applied as the models for the uncertain nonlinear systems. The nonlinear modeling process is to find the coefficients of the fuzzy equations.We use the neural networks to approximate the coefficients of the fuzzy equations.The approximation theory for ...