Reference:

Catherine Bounsaythip and Timo Honkela. Combination of neural and evolutionary methods for data organization. In Katsumi Tanaka and Shahram Ghandeharizadeh, editors, Proceedings of FODO'98, The 5th International Conference on Foundations of Data Organization, pages 20–25, 1998.

Abstract:

Fuzzy logic, articial neural network models and evolutionary computing are the main methodolog- ical tools of the soft computing area. This article provides an overview on two of them, namely neu- ral networks and evolutionary models. The largest number of applications that combine these two is based on the idea that a genetic algorithm is used to optimize the functioning of a neural network. A more general focus is taken here and examples of other kinds of combinations are given. Further- more, special emphasis is given on the combination of genetic algorithms and Kohonen's self-organizing map (SOM). The usage of the SOM in analyzing and organizing the populations produced by a GA is considered in some more detail. Finally, some applications in the Web and information retrieval domain are presented.

Suggested BibTeX entry:

@inproceedings{Bounsaythip1998,
    author = {Catherine Bounsaythip and Timo Honkela},
    booktitle = {Proceedings of FODO'98, The 5th International Conference on Foundations of Data Organization},
    editor = {Katsumi Tanaka and Shahram Ghandeharizadeh},
    pages = {20-25},
    title = {Combination of Neural and Evolutionary Methods for Data Organization},
    year = {1998},
}