Аннотация
The paper demonstrates the efficient use of hybrid
intelligent systems for solving the classification
problem of bankruptcy. The aim of the study is to
obtain classification schemes able to predict business
failure. Previous attempts to form efficient
classifiers for the same problem using intelligent or
statistical techniques are discussed throughout the
paper. The application of neural logic networks by
means of genetic programming is proposed. This is an
advantageous approach enabling the interpretation of
the network structure through set of expert rules,
which is a desirable feature for field experts. These
evolutionary neural logic networks are consisted of an
innovative hybrid intelligent methodology, by which
evolutionary programming techniques are used for
obtaining the best possible topology of a neural logic
network. The genetic programming process is guided
using a context-free grammar and indirect encoding of
the neural logic networks into the genetic programming
individuals. Indicative classification results are
presented and discussed in detail in terms of both,
classification accuracy and solution
interpretability.
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