Nearest-Neighbor Spline Approximation (NNSA) Improvement to TSK Fuzzy Systems
作者： Jordan Richardson , Janusz Korniak , Philip D. Reiner , Bogdan M. Wilamowski
关键词: Approximation algorithm 、 Fuzzy control system 、 Fuzzy set operations 、 Function approximation 、 Mathematical optimization 、 Mathematics 、 Fuzzy classification 、 Spline (mathematics) 、 Neuro-fuzzy 、 Defuzzification 、 Algorithm
摘要: In this paper, we propose two versions of an improved defuzzification technique for Takagi Sugeno Kang (TSK) fuzzy systems (FSs) based on local third-order approximations. The presented nearest-neighbor spline approximation algorithms (NNSA1 and NNSA2) use the concept a zeroth-order TSK FS produce smooth surfaces with increased accuracy. proposed methods are tested variety function problems pertaining to industrial applications against popular machine learning methodologies. Experimental results show that indeed competitive in terms computation time, accuracy, generalization ability when compared other approaches.
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