fuzzylogic computes a multi-criteria evaluation by means of either a boolean analysis, weightedlinear combination (wlc) and ordered weighted averaging (owa) of factor images. owa works withstandardized factor images and employs a variant of the wlc. it takes into account the risk associated withthe decision and degree of tradeoff associated with the variables in the analysis. in this research, ...

In this document we carry out a comparative analysis of the application of Fuzzy Logic Controllers (hereinafter FLCs), Fuzzy Temporal Rules-Based Controllers (hereinafter FTRCs), Temporal Fuzzy Logic Controllers (hereinafter TFLCs) and Faded Temporal fuzzy Logic Controllers (hereinafter FTFLCs), to improve the adaptive distributed routing. To obtain a good knowledge base the controllers were ev...

in recent years, soft computing methods have generated a large research interest. the synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. a particular evolutionary algorithm (ea) is differential evolution (de). as for any ea, de algorithm also requires parameters tuning to achieve desirable performance. in this paper tuning the perturbation factor vector of de ...

A new scheme to obtain optimal fuzzy subsets and rules is proposed. The method is derived from the use of genetic algorithms, where the genes of the chromosome are classified into two different types. These genes can be arranged in a hierarchical form, where one type of genes controls the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to b...

Based on fuzzy language field and fuzzy language value structure, a new knowledge representation frame is presented. A generalized cell automation and the corresponding generalized induction logic causal model are also proposed, which can synthetically process random and fuzzy indeterminacy. Thus, a new indeterminacy causal induction auto-reasoning mechanism is presented on the basis of fuzzy s...

This paper proposes a new intelligent scheme using type-2 fuzzy inference system in neural network structure. This type-2 fuzzy neural network system (type-2 FNN) combines the advantages of type-2 fuzzy logic systems (FLSs) and neural networks (NNs). The general FNN system (called type-1 FNN system) has the properties of parallel computation scheme, easy to implement, fuzzy logic inference syst...

The concept of Galois connection between power sets is generalized from the point of view of fuzzy logic. Studied is the case where the structure of truth values forms a complete residuated lattice. It is proved that fuzzy Galois connections are in one-to-one correspondence with binary fuzzy relations. A representation of fuzzy Galois connections by (classical) Galois connections is provided. 1...

The main idea motivating the development of fuzzy logic (FL) can be formulated as follows: Fuzzy logic is a special many-valued logic addressing the vagueness phenomenon and developing tools for its modeling via truth degrees taken from an ordered scale. It is expected to preserve as many properties of classical logic as possible. During the past 15 years, the mathematical FL has been developed...