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Contributors: Eng-Yeow Cheu, See-Kiong Ng, and Hiok-Chai Quek

School of Computer Engineering. Presented by: Division of Computer Science Centre for Computational Intelligence. An Interval Type-2 Neural Fuzzy Inference System based on Piaget’s Action-Cognitive Paradigm Objective

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Contributors: Eng-Yeow Cheu, See-Kiong Ng, and Hiok-Chai Quek

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  1. School of Computer Engineering Presented by:Division of Computer Science Centre for Computational Intelligence • An Interval Type-2 Neural Fuzzy Inference System based on Piaget’s Action-Cognitive Paradigm • Objective • To construct fuzzy model from cognitive development and biological neuronal level. • To support cognitive reasoning with imprecise information under linguistic and numerical uncertainties. • Approach • Data-driven interval type-2 Neural Fuzzy Inference System that is able to automatically acquire the linguistic model to support cognitive reasoning with imprecise information under additional uncertainties. • Result Learning Method Structure of interval type-2 Neural Fuzzy Inference System Action-Driven Structure Identification Actions Specification Formation of scatter-based input fuzzy partitions Adaptation of input fuzzy partitions Prune overlapping input fuzzy partitions Rule generation Parameter Tuning Example: Nonlinear System Interval Type-2 Membership Functions (MF) Input 1 MFs Input 2 MFs Output MFs Contributors: Eng-Yeow Cheu, See-Kiong Ng, and Hiok-Chai Quek www.ntu.edu.sg

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