Evolutionary training of behavior-based self-organizing map
| Autor: | H. Hyotyniemi, A.S. Nissinen |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Self-organizing map
Theoretical computer science Cover (topology) business.industry Computer science Computer Science::Neural and Evolutionary Computation Metric (mathematics) Parameterized complexity Sample (statistics) Artificial intelligence business Evolutionary computation Interpretation (model theory) |
| Zdroj: | 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360). |
| Popis: | The paper presents a novel idea of a behavior-based self-organizing map. The self-organizing map (SOM) is extended to cover 'objects' that interact with their environment. They are organized based on their behavior instead of parameterized presentation. The original SOM needs a metric to be defined, while in the new self-organizing map no metric between the parameterized presentations is needed. The neighborhood concept of the SOM algorithm is given a probability interpretation that is suitable for evolutionary computing. The behavior based SOM algorithm is presented, and the new concept is demonstrated on linear time-series models, that are identified and organized based on sample data from a simulated system. |
| Databáze: | OpenAIRE |
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