Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/530
Title: An ontology-based knowledge management system for flow and water quality modeling
Authors: Chau, KW 
Keywords: Knowledge management system
Flow and water quality modeling
Artificial intelligence
Ontology-based
Issue Date: Mar-2007
Publisher: Elsevier
Source: Advances in engineering software, Mar. 2007, v. 38. no. 3, p. 172-181 How to cite?
Journal: Advances in engineering software 
Abstract: Currently, the numerical simulation of flow and/or water quality becomes more and more sophisticated. There arises a demand on the integration of recent knowledge management (KM), artificial intelligence technology with the conventional hydraulic algorithmic models in order to assist novice application users in selection and manipulation of various mathematical tools. In this paper, an ontology-based KM system (KMS) is presented, which employs a three-stage life cycle for the ontology design and a Java/XML-based scheme for automatically generating knowledge search components. The prototype KMS on flow and water quality is addressed to simulate human expertise during the problem solving by incorporating artificial intelligence and coupling various descriptive knowledge, procedural knowledge and reasoning knowledge involved in the coastal hydraulic and transport processes. The ontology is divided into information ontology and domain ontology in order to realize the objective of semantic match for knowledge search. The architecture, the development and the implementation of the prototype system are described in details. Both forward chaining and backward chaining are used collectively during the inference process. In order to demonstrate the application of the prototype KMS, a case study is presented.
URI: http://hdl.handle.net/10397/530
ISSN: 0965-9978
DOI: 10.1016/j.advengsoft.2006.07.003
Rights: Advances in Engineering Software © 2006 Elsevier Science. The journal web site is located at http://www.sciencedirect.com.
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