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A prototype-based rule inference system incorporating linear functions. (English) Zbl 1207.68392
Summary: A calculus of appropriateness measures of linguistic expressions is proposed, which is based on the prototype theory and random set theory interpretation of vague concepts. A prototype-based rule inference system is then introduced to incorporate linguistic labels in the rule antecedents and linear functions in the consequents of rules. A rule learning algorithm is developed by combining a new clustering algorithm and a conjugate gradient algorithm. The proposed prototype-based inference system is then applied to a number of benchmark prediction problems including a nonlinear two-dimensional surface, the Mackey-Glass time series and the sunspot time-series. Results suggest that the proposed model is very robust and can perform well in high-dimensional noisy data.

##### MSC:
 68T37 Reasoning under uncertainty in the context of artificial intelligence
##### Software:
ANFIS; LFOIL; TDSL; TSDL
Full Text:
##### References:
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