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2 International Journal of Applied Mathematics and Computer Science

2 Simiński K.

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Rule weights in a neuro-fuzzy system with a hierarchical domain partition

100%

Simiński K.

International Journal of Applied Mathematics and Computer Science

2010

tom 20

nr 2

337-347

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.

Neuro-rough-fuzzy approach for regression modelling from missing data

100%

Simiński K.

nr 2

461-476

Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answer for full and missing data examples. The paper also describes the dedicated clustering algorithm. The paper is accompanied by results of numerical experiments.