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- W2126331036 abstract "This paper introduces a novel neuro-fuzzy inference system denoted as ldquoMUFIS: a neuro-fuzzy inference system using multiple types of fuzzy rulesrdquo, for allowing multiple types of fuzzy rules to be used together to achieve a better performance. At each data point, the output of MUFIS is calculated through a fuzzy inference system based on m-most activated fuzzy rules which are dynamically chosen from multi-type fuzzy rules. It is demonstrated that MUFIS can effectively implement prediction and function approximation. We evaluate its performance on two case studies - a benchmark time-series prediction problem - Mackey Glass, and a real life medical prediction problem - glomerular filtration rate prediction." @default.
- W2126331036 created "2016-06-24" @default.
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- W2126331036 date "2008-06-01" @default.
- W2126331036 modified "2023-09-27" @default.
- W2126331036 title "MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules" @default.
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- W2126331036 doi "https://doi.org/10.1109/fuzzy.2008.4630556" @default.
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