Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation
International Journal of Approximate Reasoning
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Information Sciences: an International Journal
Computers and Industrial Engineering
Quantale-based autoassociative memories with an application to the storage of color images
Pattern Recognition Letters
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We introduce novel (set- and lattice-theoretic) perspectives and tools for the analysis and design of fuzzy inference systems (FISs). We present an FIS, including both fuzzification and defuzzification, as a device for implementing a function f: RNrarr RM. The family of FIS functions has cardinality aleph2=2aleph1, where aleph1 is the cardinality of the set R of real numbers. Hence the FIS family is much larger than polynomials, neural networks, etc.; furthermore a FIS has a capacity for local generalization. A formulation in the context of lattice theory allows us to define the set F* of fuzzy interval numbers (FINs), which includes both (fuzzy) numbers and intervals. We present a metric dK on F*, which can introduce tunable nonlinearities. FIS design based on dK has advantages such as: an alleviation of the curse of dimensionality problem and a potential for improved computer memory utilization. We present a new FIS classifier, namely granular self-organizing map (grSOM), which we apply to an industrial fertilizer modeling application