Abstract
The paper introduces neuro-fuzzy modeling to the problem of controlling interstate conflict. It is shown that a neuro-fuzzy model achieves a prediction accuracy similar to Bayesian trained neural networks. It is further illustrated that a neuro-fuzzy model can be used in a Genetic Algorithm (GA) based control scheme to avoid 100% of the detected conflict cases. The neuro-fuzzy model is then suggested as a more suitable option to neural networks as the model offers information transparency in the form of fuzzy rules, as compared to the weights of the neural network.
| Original language | English |
|---|---|
| Title of host publication | INES 2006 |
| Subtitle of host publication | 10th International Conference on Intelligent Engineering Systems 2006 |
| Pages | 30-34 |
| Number of pages | 5 |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | INES 2006: 10th International Conference on Intelligent Engineering Systems 2006 - London, United Kingdom Duration: 26 Jun 2006 → 28 Jun 2006 |
Publication series
| Name | INES 2006: 10th International Conference on Intelligent Engineering Systems 2006 |
|---|
Conference
| Conference | INES 2006: 10th International Conference on Intelligent Engineering Systems 2006 |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 26/06/06 → 28/06/06 |
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Applied Mathematics
- Theoretical Computer Science
