Keywords: integrated knowledge-based systems, KBS, water quality, flow, Hong Kong waters, numerical models, environmental pollution, artificial neural networks, fuzzy inference system, artificial intelligence, simulation
Development of an integrated knowledge-based system on flow and water quality in Hong Kong coastal waters
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.