The structure of the TS fuzzy system can also be represented as a neural network with a specific (five layer) composition (Fig. (TS) form is represented by mathematical functions (usually linear). The consequent part of the fuzzy rules in the so‐called Takagi–Sugeno The most popular membership functions are Gaussian, triangular, trapezoidal . It can be mathematically described by so‐called t‐norms or t‑conorms between membership functions. In the above example, a conjunction (logical AND) is used. The antecedent part consists of a number of fuzzy sets that are linked with fuzzy logic aggregators such as conjunction, disjunction, more rarely, negation .
Each fuzzy rule is composed of antecedent (IF) and consequents (THEN) parts. Structure of a fuzzy (or neuro‐fuzzy) system is constituted of a set of fuzzy rules ( 1). Of the underlying (fuzzy or neuro‐fuzzy) system structure. ) systems do not deal with such phenomena. The terms evolutionary or geneticĪre also associated with such phenomena (respectively operators that mimic these) as chromosome crossover, mutation,selection and reproduction, parents andoff‐springs . ” in the same source, which is “development of more complicated forms of life (plants, animals) from earlier and simpler forms”. Contrast this to the definition of “evolutionary In this sense, this definition strictly follows the meaning of the English word “evolving” as described in , p. 294, namely “unfolding developing being developed, naturally and gradually”.
0 kommentar(er)
