This contribution proposes a new model for sentiment analysis, which combines the convolutional neural network (CNN), C4.5 decision tree algorithm, and Fuzzy Rule-Based System (FRBS). Our suggested method consists of six parts. Firstly we have applied several pre-processing techniques. Secondly, used fastText vectoring analysed tweets. Thirdly, implemented CNN extracting selecting pertinent fea...

this paper we explore the use of weights in the generation of fuzzy models. We automatically generate a fuzzy model, using a three-stage methodology: (i) generation of a crisp model from a decision tree, induced from the data, (ii) transformation of the crisp model into a fuzzy one, and (iii) optimization of the fuzzy model's parameters. Based on this methodology, the generated fuzzy model incl...

A fuzzification of the concept of functional dependency based on t-norms is presented. T-norms are equally used in the definition of the similarity relations in the domains and in the fuzziness degree assigned to functional dependencies. A sound and complete logic for this fuzzy functional dependencies is also introduced and, finally, its applicability to redundancy removing is shown.

The main goal of this work is to analyze the behaviour of the F quantifier fuzzification mechanism [23, 22, 17]. As we prove in the paper, this model has a very solid theorethical behaviour, superior to most of the models defined in the literature. Moreover, we show that the underlying probabilistic interpretation has very interesting consequences.

We consider the fuzzification of the notion of an n-fold implicative ideal, an n-fold (weak) commutative ideal. We give characterizations of an n-fold fuzzy implicative ideal. We establish an extension property for n-fold fuzzy commutative ideals. 2000 Mathematics Subject Classification. 06F35, 03G25, 03E72.

In [4] we have presented a new common platform for different types of fuzzification of a concept lattice. Now we show a pendant of the basic theorem on clasical concept lattices for this generalization which characterizes (complete) lattices isomorphic to this generalized concept lattice.

A fuzzy microcontroller is presented implementing a simplified inference mechanism. Fuzzification, rule composition and defuzzification are carried out by means of (basically) analog current-mode CMOS circuits operating in strong inversion. Also a voltage interface is provided with the external world. Combining analog and digital techniques allow a programming capability.

We introduce MK-fuzzy automata over a bimonoid K which is related to the fuzzification of the McCarthy-Kleene logic. Our automata are inspired by, and intend to contribute to, practical applications being in development in the LogicGuard project [15, 16]. We investigate closure properties of the class of MK-fuzzy languages accepted by MK-fuzzy automata as well as by their deterministic counterp...