MIST (Model Identification and Selection Tool): A Knowledge-Based System for Selection of Water Quality Models
Publication: Towards a Vision for Information Technology in Civil Engineering
Abstract
A Knowledge-based system, MIST (Model Identification and Selection Tool), is developed for selection of water quality models. A knowledge base is set up using information collected from a number of manuals, literature searches, to facilitate this selection process. The knowledge is then codified into a knowledge-base that can be used within a knowledge-based system. A knowledge-base skeleton, M.4, is used as a backbone to develop the system. The knowledgebase skeleton provides a mechanism to develop rules in production rule format, and includes forward and backward chaining goal seeking mechanisms, and allows the user to provide confidence/certainty factors to the answers provided in the process of consultation. The front-end of the decision support system is developed using integrated development environment (IDE) under visual basic (VB) programming to provide a graphical interface for the end user. MIST consists of a number of modules (knowledge-bases) that are relevant to few classes of modeling environments. Results suggest that MIST can be used as a model selection tool for inexperienced modelers.
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Copyright
© 2004 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Bibliographies
- Business management
- Computer programming
- Computing in civil engineering
- Consulting services
- Data collection
- Decision making
- Decision support systems
- Engineering fundamentals
- Environmental engineering
- Graphic methods
- Information management
- Knowledge-based systems
- Methodology (by type)
- Practice and Profession
- Professional services
- Research methods (by type)
- Water quality
- Water treatment
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