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Title: Fuzzy logic knowledge bases in integrated landscape assessment: examples and possibilities.

Author: Reynolds, Keith M.;

Date: 2001

Source: Gen. Tech. Rep. PNW-GTR-521. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 24 p

Publication Series: General Technical Report (GTR)

Description: The literature on ecosystem management has articulated the need for integration across disciplines and spatial scales, but convincing demonstrations of integrated analysis to support ecosystem management are lacking. This paper focuses on integrated ecological assessment because ecosystem management fundamentally is concerned with integrated management, which presupposes integrated analysis. Knowledge-based solutions are particularly relevant to ecosystem management because the topic is conceptually broad and complex and involves many abstract concepts whose assessment depends on many interdependent states and processes. Logic constructs are useful in this context because the problem can be evaluated as long as the entities and their logical relations are understood in a general way and can be expressed by subject matter authorities. As an example, ecosystem management decision-support system provides a formal logic framework for integrated analysis across multiple problem domains, has the ability to reason with incomplete information, and assists with optimizing the conduct of assessments by setting priorities on missing data. Most significant, however, is the possibility that knowledge-based reasoning could readily be extended to networks of knowledge bases that provide logical specifications for integrated analysis across spatial scales.

Keywords: Knowledge base, fuzzy logic, hierarchy, network, integration, ecosystem management, ecological assessment, landscape analysis

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Citation:


Reynolds, Keith M. 2001. Fuzzy logic knowledge bases in integrated landscape assessment: examples and possibilities. Gen. Tech. Rep. PNW-GTR-521. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 24 p

 


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