Abstract
This paper describes,an ongoing work on the application of machine learning techniques in the domain of water distribution networks. This research is being done in the context of the European Esprit project Waternet. One part of this project is a learning system which intends to capture knowledge from historic information collected during the operation of a water distribution network. Captured knowledge is expected to contribute to improve the operation of the network. The ideas presented in this paper describe the first development phase of this learning system, focusing specially in the practical methodology adopted. The interaction between different classes of human experts and the learning system are discussed. Finally some preliminary experimental results are presented.
| Original language | English |
|---|---|
| Title of host publication | Intelligent systems for manufacturing: multi-agent systems and virtual organization |
| Editors | LM CamarinhaMatos, H Afsarmanesh, Marik |
| Publisher | Kluwer Academic Publishers |
| Pages | 121-136 |
| Number of pages | 16 |
| ISBN (Print) | 0-412-84670-5 |
| Publication status | Published - 1998 |
| Event | 3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing - PRAGUE, Czech Republic Duration: 1 Aug 1998 → … |
Conference
| Conference | 3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing |
|---|---|
| Country | Czech Republic |
| City | PRAGUE |
| Period | 1/08/98 → … |
Keywords
- machine learning
- water distribution network
- knowledge acquisition
- forecasting