本文研究之目的为将近年来先进的人工智能技术与现有的数学模型互相结合,开发一套有关海域水流及水质之综合智能型系统。其应用之技术包括智能型系统、人工神经网络及模糊推理系统。此系统可作辅助设计或训练之工具,能帮助水力及环境工程师熟习最先进的海域水流及水质模型,以期使科研与实际执行者之间的距离缩小。其结果可导致对各种不同方式数学模型之好处、应用或限制,有更透彻的了解,甚至从而达成突破及贡献。随着环境可持续性愈来愈被重视,对开发此类综合系统之需求亦逐渐增加,正好可辅助决策者迅速地达成决定,并同时可向公众提供方便及公开的水质信息。||This work aims to study how to couple the recent advancements in artificial intelligence (AI) technology with existing numerical models to constitute an integrated knowledge-based system on flow and water quality. This hybrid application of the latest AI technologies, namely, knowledge-based system, artificial neural network, and fuzzy inference 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 Kong Kong. Consequently, this may lead to a better understanding of the advantages, applicability and limitations of the different methodologies or even contributions in methodologies and theories. With an increasing concern over the issue of environmental sustainability, there has emerged a 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.
|Number of pages||4|
|Journal||力学季刊 (Chinese quarterly of mechanics)|
|Publication status||Published - 2005|
- Knowledge-based system
- Flow and water quality
- Artificial inteligence
- Mathematical models