T he concept of fuzzy integral was initiated by Dubois and Prade [11] and then investigated by Kaleva [21], Goetschel and Voxman [20], Nanda [23] and others. In [33], the Henstock integral of fuzzy-valued functions is defined, while the fuzzy Riemann integral and its numerical integration was investigated byWu in [34]. In [7], the authors introduced some quadrature rules for the integral of fuz...

In order to exploit the nonlinear time-varying property of network traffic, the traffic flow from controlled sources is described by a fuzzy autoregressive moving-average model with auxiliary input (fuzzy ARMAX process), with the traffic flow from uncontrolled sources (i.e., cross traffic) being described as external disturbances. In order to overcome the difficulty of the transmission delay in...

A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. This paper discusses the identification of the parameters at the antecedent and consequent parts of the fuzzy model. For the antecedent fuzzy parameters, genetic algorithm is used to tune ...

An important issue in the design of FRBS is the formation of fuzzy if-then rules and the membership functions. This paper presents a Mixed Genetic Algorithm (MGA) approach to obtain the optimal rule set and the membership function of the fuzzy classifier. While applying genetic algorithm for fuzzy classifier design, the membership functions are represented as real numbers and the fuzzy rules ar...

Fuzzy rule-based systems have been mainly used as a convenient tool for synthesizing control laws from data. Recently, in a knowledge representation-oriented perspective, a typology of fuzzy rules has been laid bare, by emphasizing the distinction between implicative and conjunctive fuzzy rules. The former describe pieces of generic knowledge either tainted with uncertainty or tolerant to simil...

This paper presents genetic algorithms (GAs) to perform the optimal design of an auto-tuning fuzzy proportional-integral-derivative (PID) controller and to determine the minimal number of fuzzy rules simultaneously. Different from PID controllers with fixed gains, the fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivati...

Case-based reasoning (CBR) attempts to solve new problems by using previous experiences. However traditional CBR systems are restricted by the similarity requirement, i.e., the availability of similar cases to new problems. This paper proposes a novel CBR approach that exploits dissimilarity information in problem solving. A fuzzy dissimilarity model consisting of fuzzy rules has been developed...

In our real life, bipolar fuzzy theory is a core feature to be considered: positive information represents what is possible or preferred, while negative information represents what is forbidden or surely false. In this paper, we provide a general algebraic framework for handling bipolar information by combining the theory of bipolar fuzzy sets with hemirings. First, we present the concepts of b...

An approach based on multi-objective genetic algorithms is proposed to construct interpretable and precision fuzzy classification system from data. First, a multi-objective genetic algorithm is used to accomplish feature selection and dynamic grid partition with three objectives: maximization of precision, minimization of the number of features, and minimization of the number of fuzzy rules. Th...

Although 12-step literature posits inconsiderate behaviors to characterize alcoholics and addicts, there is little data to support this association among adolescent populations. Using a matched-pair study design with 579 youth aged 14-18 (52% female, 30% minority), a significant, dose-response relationship was found between greater alcohol and drug use severity and increased likelihood of drivi...