Fuzzy inference process usually involves the use of fuzzy rule base consisting in several fuzzy rules. Overall output can be obtained by aggregation of outputs of all rules. To ob...
— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
: Classical classification and clustering based on equivalence relations are very important tools in decision-making. An equivalence relation is usually determined by properties of...
By exploiting the Fourier series expansion, we have developed a new constructive method of automatically generating a multivariable fuzzy inference system from any given sample set...
The need for an automatic inference process able to deal with information coming from unreliable sources is becoming a relevant issue both on corporate networks and on the open Web...