Rough set-based Neuro-Fuzzy System
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Описание:
Neuro-fuzzy systems is a popular hybridization in soft computing that abstracts a fuzzy model from given numerical examples using neural learning techniques to formulate accurate predictions on unseen samples. The fuzzy model incorporates the human-like style of fuzzy reasoning through a linguistic model that comprises if-then fuzzy rules and linguistic terms described by membership functions. However, modeling data using neuro-fuzzy systems involves the contradictory requirements of interpretability versus accuracy. This monograph focuses on increasing interpretability without compromising accuracy using a novel hybrid intelligent Rough set-based Neuro-Fuzzy System (RNFS), which synergizes rough set-based knowledge reduction with neuro-fuzzy systems. RNFS employs novel bio-inspired algorithms to generate human- interpretable membership functions from numerical data, and rough set-based algorithm to identify fewer if-then fuzzy rules that facilitate human interpretation. Example...Похожие книги
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