AI - a Guide to Intelligent Systems.pdf - Member of EEPIS

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HYBRID INTELLIGENT SYSTEMS
Figure 8.18
The evolutionary cycle of evolving a neural network topology
8.6 Fuzzy evolutionary systems
Evolutionary computation is also used in the design of fuzzy systems, particularly
for generating fuzzy rules and adjusting membership functions of fuzzy sets.
In this section, we introduce an application of genetic algorithms to select an
appropriate set of fuzzy IF-THEN rules for a classification problem (Ishibuchi
et al., 1995).
To apply genetic algorithms, we need to have a population of feasible
solutions – in our case, a set of fuzzy IF-THEN rules. We need to obtain this set.
For a classification problem, a set of fuzzy IF-THEN rules can be generated from
numerical data (Ishibuchi et al., 1992). First, we use a grid-type fuzzy partition
of an input space.
Figure 8.19 shows an example of the fuzzy partition of a two-dimensional
input space into 3 3 fuzzy subspaces. Black and white dots here denote the
training patterns of Class 1 and Class 2, respectively. The grid-type fuzzy