Application of machine learning techniques in water distribution networks assisted by domain experts

LM Camarinha-Matos, FJ Martinelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationIntelligent systems for manufacturing: multi-agent systems and virtual organization
EditorsLM CamarinhaMatos, H Afsarmanesh, Marik
PublisherKluwer Academic Publishers
Pages121-136
Number of pages16
ISBN (Print)0-412-84670-5
Publication statusPublished - 1998
Event3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing - PRAGUE, Czech Republic
Duration: 1 Aug 1998 → …

Conference

Conference3rd IEEE/IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing
CountryCzech Republic
CityPRAGUE
Period1/08/98 → …

Keywords

  • machine learning
  • water distribution network
  • knowledge acquisition
  • forecasting

Cite this

Camarinha-Matos, LM., & Martinelli, FJ. (1998). Application of machine learning techniques in water distribution networks assisted by domain experts. In LM. CamarinhaMatos, H. Afsarmanesh, & Marik (Eds.), Intelligent systems for manufacturing: multi-agent systems and virtual organization (pp. 121-136). Kluwer Academic Publishers.