LISP or CLIPS: Selecting an Expert System Tool in Hydraulic Engineering

by Nosrat Maghsoudi, Consulting Hydraulic Engineer, Lafayette, United States,
D. B. Simons, Consulting Hydraulic Engineer, Lafayette, United States,

Document Type: Proceeding Paper

Part of: Hydraulic Engineering


The transfer of Artificial Intelligence(AI) technology from the research laboratories to the scientific and engineering environments has been made possible by phenomenal advances in computer hardware and software technologies in recent years. Expert Systems (ES), a branch of AI, experienced explosive growth and popularity in the last decade. Now, ES is one of the most important areas of AI with established success in many disciplines including hydraulic engineering and water resources. Demonstrated success of ES has encouraged the development and marketing of many ES building tools with different features, functions, and levels of complexity. Considering the nature of knowledge domain in different areas of hydraulic engineering on the one hand, and the capabilities and limitations of available ES building tools on the other, a methodology is presented to determine the required features of each area and to select the most appropriate ES building tool.

Subject Headings: Hydraulic engineering | Expert systems | Systems engineering | Hydraulic networks | Artificial intelligence and machine learning | Computer languages | Smart buildings | Computing in civil engineering

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