Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1239
PIRA download icon_1.1View/Download Full Text
Title: An intelligent knowledge processing system on hydrodynamics and water quality modeling
Authors: Chau, KW 
Cheng, C
Li, YS 
Li, CW 
Wai, WHO 
Issue Date: 2002
Source: In T Hendtlas & M Ali (Eds.), Developments in applied artificial intelligence : 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2002, Cairns, Australia, June 2002 : proceedings, p. 670-679. Berlin ; New York: Springer, 2002
Abstract: In order to aid novice users in the proper selection and application of myriad ever-complicated algorithmic models on coastal processes, needs arise on the incorporation of the recent artificial intelligence technology into them. This paper delineates an intelligent knowledge processing system on hydrodynamics and water quality modeling to emulate expert heuristic reasoning during the problem-solving process by integration of the pertinent descriptive, procedural, and reasoning knowledge. This prototype system is implemented using a hybrid expert system shell, Visual Rule Studio, which acts as an ActiveX Designer under the Microsoft Visual Basic programming environment. The architecture, solution strategies and development techniques of the system are also presented. The domain knowledge is represented in object-oriented programming and production rules, depending on its nature. Solution can be generated automatically through its robust inference mechanism. By custom-built interactive graphical user interfaces, it is capable to assist model users by furnishing with much needed expertise.
Keywords: Water quality modelling
Artificial intelligence
Hydrodynamics
Publisher: Springer
ISBN: 978-3-540-43781-9
DOI: 10.1007/3-540-48035-8_65
Description: Series: Lecture notes in computer science
Rights: © Springer-Verlag Berlin Heidelberg 2002. The original publication is available at http://www.springerlink.com.
Appears in Collections:Book Chapter

Files in This Item:
File Description SizeFormat 
LNAI3.pdfPre-published version195.35 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

136
Last Week
0
Last month
Citations as of Mar 24, 2024

Downloads

148
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

2
Last Week
0
Last month
Citations as of Mar 29, 2024

WEB OF SCIENCETM
Citations

2
Last Week
0
Last month
0
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.