Open AccessTHE INSTANCE SELECTION METHOD FOR NEURO-FUZZY MODEL SYNTHESIS
Author(s) -
С. А. Субботин
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.13.3.630
Subject(s) - computer science , generalization , selection (genetic algorithm) , set (abstract data type) , neuro fuzzy , fuzzy logic , transformation (genetics) , sample (material) , software , data mining , artificial intelligence , algorithm , fuzzy control system , mathematics , mathematical analysis , biochemistry , chemistry , programming language , chromatography , gene
The problem of automation of neuro-fuzzy model synthesis on instance set is addressed. The method of instance selection for neuro-fuzzy model synthesis is proposed. It allows reducing the sample size, and decreasing the requirements to computer resources. The method also performs transformation of the original multi-dimensional coordinate set to the one-dimensional axis, which is also discretized to improve the data generalization properties. The software implementing proposed method is developed. The experiments were conducted to study the proposed method at the real problem solution. The results of experiments allow recommending proposed method for usage at practice.