Titlebook: Artificial Intelligence for Biology and Agriculture; S. Panigrahi,K. C. Ting Book 1998 Springer Science+Business Media Dordrecht 1998 arti

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978-94-010-6120-9Springer Science+Business Media Dordrecht 1998

彎腰

Fuzzy Logic for Biological and Agricultural Systems,precise relationships for modeling system behavior. The paper presents an overview of fuzzy logic modeling techniques, its applications to biological and agricultural systems and an example showing the steps of constructing a fuzzy logic model.

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政府

,Truck Platooning – A Pragmatical Approach,ucts. The approach involves reasoning about the reuse of both qualitative and mathematical models for physiolog ical processes, and constructs quantitative simulation models for the postharvest behaviour of agricultural products. The qualitative models are used to bridge the gap between the modeller

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ANIM

Markus Maurer,Christoph Stillerntional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involv

Anthology

Dislocation

Lang-Lkw per Fernbedienung rangierenpossibilities of the system, where different image sequences will be treated. The motion issue involves three aspects: image segmentation, object tracking and motion analysis. The current system version focuses mainly on the image segmentation aspect. A general agent model has been designed, which w