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Interval-Based Parameter Recognition with the Trends in Multiple Estimations

Interval-Based Parameter Recognition with the Trends in Multiple Estimations,V. Terziyan,S. Puuronen,H. Kaykova

Interval-Based Parameter Recognition with the Trends in Multiple Estimations  
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This paper considers the context sensitive approach to handle interval knowledge acquired from multiple knowledge sources. Each source gives its estimation of the value of some parameter x. The goal is to process all the intervals in a context of trends caused by some noise and derive resulting estimation that is more precise than the original ones and also takes into account the context noise. The main assumption used is that if a knowledge source guarantees smaller measurement error (estimated interval is shorter) then this source in the same time is more resistant against the effect of noise. This assumption allows us to derive and process trends among intervals and end up to shorter resulting estimated interval than any of the original ones.
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