Uhrmacher, Adelinde M. and Cellier, François E. and Frye, R.J. (1997) Applying fuzzy-based inductive reasoning to analyze qualitatively the dynamic behavior of an ecological system. AI Applications, 11 (2), pp. 1-10. ISSN 1051-8266.
Full text not available from this repository.Abstract
Qualitative reasoning methodologies are an alternative to quantitative modeling approaches if the knowledge about the system of interest is imprecise or incomplete, as is often the case with ecological systems. In Biosphere 2, a closed ecological system, the level of O2 dropped and the CO2 level rose continously during its closure betwen 1991 and 1993. The mechanisms of carbon cycles have been subject to multiple research efforts and are therefore formulated as general rules in principle. However, the structure of the carbon cycle in Biosphere 2 is not well known, although abundant data exist on some of the important fluxes and pools. While deductive methodologies require knowledge about the structure of the system to derive the behavior of the system, the fuzzy-based inductive reasoning methodology, FIR, derives a behavior model inductively by analyzing time series. The derived behavior model comprises cases and information about how to retrieve prototypical cases that can be adapted to the given situation. Thus, FIR combines one-shot inductive and incremental case-based reasoning techniques to analyze and forecast dyanmic systems.
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