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Lesson Navigation IconIntermediate Suitability Analysis

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Unit Navigation IconMulti-objective analysis

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A type of imprecision characterising classes that for various reasons cannot have or do not have sharply defined boundaries. The term fuzzy may cause misconceptions. "Fuzzy" is said to have a negative connotation, usually suggesting something imprecise. However, fuzzy logic is not any less imprecise than other forms of logic, but rather is an organized and mathematical method of handling inherently uncertain information.
Fuzzy membership function (FMF):
A function describing the degree of membership (d.o.m.) of an entity to a class with inexactly defined boundaries (fuzzy set).
Fuzzy overlay:
Fuzzy overlay results from applying fuzzy logic to spatial overlay. Fuzzy overlay hence combines for a given location not certainty values (e.g., steep slope AND densely forested), but rather values indicating uncertain, i.e. fuzzy, memberships to slope and forestation classes (e.g., membership for steep slope is 0.8, membership for densely forested is 0.7).
Fuzzy sets:
Inexactly defined classes, i.e. classes that cannot or do not have sharply defined boundaries.
Procedure designed to solve a problem that ignores whether the solution is provably correct, but which usually produces a good solution or solves a simpler problem that contains or intersects with the solution of the more complex problem. It is a "rule of thumb", based on experience or experiments rather than on a formal solution. The term comes from the same Greek root "euriskw" as "eureka" meaning "to find". (Wikipedia)
Multi-criteria evaluations (MCE):
Suitability analysis that satisfies several criteria with respect to a single objective.
Multi-objective evaluation (MOE):
Suitability analysis that satisfies several, possibly conflicting objectives.
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