The purpose of this study is to investigate the accuracy of predictions of aniline removal efficiency in a moving bed biofilm reactor (MBBR) by various methods, namely by RBF, ANFIS, and fuzzy regression analysis. The reactor was operated in an aerobic batch and was filled by light expanded clay aggregate (LECA) as a carrier for the treatment of Aniline synthetic wastewater. Exploratory data an...

In this paper, we shall introduce generalized fuzzy compactness in L-spaces where L is a complete de Morgan algebra. This definition does not rely on the structure of basis lattice L and no distributivity is required. The intersection of a generalized fuzzy compact L-set and a generalized closed Lset is a generalized fuzzy compact L-set. The generalized irresolute image of a generalized fuzzy c...

this article proposes composition of fuzzy sets theory with discrete-event simulation and puts it into application in order to model uncertain activity duration in simulating a real-world system. the purpose of this paper is to assess the usefulness of fuzzy simulation for modeling uncertain activity duration, especially when insufficient or no sample data is available. in this research, fuzzy ...

In this paper, we discussed about the intuitionistic fuzzy linear transformations (IFLT) and shown that the set of all linear transformations ) (V L defined over an intuitionistic fuzzy vector space V does not form an vector space. Here we determine the unique intuitionistic fuzzy matrix associated with an intuitionistic fuzzy linear transformation with respect to an ordered standard basis for ...

A neuro-fuzzy system based on a radial basis function network and using support vector learning is considered for non-linear modeling. In order to reduce the number of fuzzy rules, and improve the system interpretability, the proposed method proceeds in two phases. Firstly, the input-output data is clustered according to the subtractive clustering method. Secondly the parameters of the network,...

Two training algorithms for self-evolving neural networks are discussed for rule-based data analysis. Efficient classification is achieved with a fewer number of automatically added clusters, and application data is analyzed by interpreting the trained neural network as a fuzzy rule-based system. The learning vector quantization algorithm has been modifified, acquiring the self-evolvement chara...

The dynamic characteristics of autonomous underwater vehicles (AUVs) present a control problem that classical methods cannot often accommodate easily. Fundamentally, AUV dynamics are highly non-linear, and the relative similarity between the linear and angular velocities about each degree of freedom means that control schemes employed within other flight vehicles are not always applicable. In s...

Universal approximation is the basis of theoretical research and practical applications of fuzzy systems. Studies on the universal approximation capability of fuzzy systems have achieved great progress in recent years. In this paper, linear Takagi–Sugeno (T–S) fuzzy systems that use linear functions of input variables as rule consequent and their special case named simplified fuzzy systems that...

This paper introduces the idea of viewing fuzzy modelling and fuzzy system design from a functional analysis perspective. Fuzzy transforms, which are based on the generalised Fourier transform in functional analysis, are proposed. It is demonstrated that, mathematically, a T-S fuzzy model is equivalent to a fuzzy transform. Hence the parameters of a T-S fuzzy system can be identified by solving...

the paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. some mathematical vector models were obtained for control system multicriterion quality indices with due ...