Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1135
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Title: Development of an integrated knowledge-based system on flow and water quality in Hong Kong coastal waters
Authors: Chau, KW 
Issue Date: 2006
Source: International journal of environment and pollution, 2006, v. 28, no. 3/4, p. 297-309
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 both as a design aid as well as a training tool, is able to allow 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 also furnish convenient and open information service on water quality for the general public.
Keywords: Integrated knowledge-based system
Water quality
Flow
Hong Kong waters
Numerical model
Publisher: Inderscience
Journal: International journal of environment and pollution 
ISSN: 0957-4352 (print)
1741-5101 (online)
DOI: 10.1504/IJEP.2006.011213
Rights: Copyright © 2006 Inderscience Enterprises Ltd. The journal web page at: http://www.inderscience.com/browse/index.php?journalID=9.
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