Abstract
This paper presents the coupling of the recent advancements in artificial intelligence (AI) technology with existing numerical models to constitute an integrated knowledge-based system (KBS) on flow and water quality. A hybrid application of the latest AI technologies, namely, KBS, artificial neural network and fuzzy inference system, in this specific problem domain is adopted here. This prototype system, serving as both a design aid as well as a training tool, enables hydraulic engineers and environmental engineers to become acquainted with up-to-date flow and water quality simulation tools, and fill the existing gaps between researchers and practitioners in the application of recent technology in solving real prototype problems in Hong Kong. Moreover, the system can meet the demand for an integrated system that can quickly assist policy makers in reaching decisions and furnish convenient and open information service on water quality for the general public.
| Original language | English |
|---|---|
| Pages (from-to) | 297-309 |
| Number of pages | 13 |
| Journal | International Journal of Environment and Pollution |
| Volume | 28 |
| Issue number | 3-4 |
| DOIs | |
| Publication status | Published - 18 Dec 2006 |
Keywords
- Flow
- Hong Kong waters
- Integrated knowledge-based system
- Numerical model
- Water quality
ASJC Scopus subject areas
- General Environmental Science
- Environmental Chemistry
- Pollution