HR: 0830h
AN: H11F-0915    [PDF]
TI: A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information
AU: * Ozbek, M M
EM: ozbek@uvm.edu
AF: University of Vermont, Department of Civil and Environmental Engineering, Burlington, VT 05401 United States
AB: Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ
DE: 1829 Groundwater hydrology
DE: 1831 Groundwater quality
DE: 1894 Instruments and techniques
SC: Hydrology [H]
MN: 2003 Fall Meeting