Fuzzy Modeling in the Agro-Climatic Domain

نویسندگان

Mercedes Valdés-Vela

Juan A. Botía Blaya

Antonio F. Gómez-Skarmeta

چکیده

Fuzzy Modeling is an effective approach for System Identification. In its turn, Data Driven Fuzzy Modeling (DDFM) extracts these models from a set of input-output observations about the system. One way to carry out a DDFM process is by means of a combination of techniques, each one solving one of the DDFM phases. In this paper, we apply hybridizations of clustering algorithms and neural networks (NN) in order to solve regression problems in the agro-climatic domain.

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