New Findings on Networks Described by Investigators at University of Suwon (Design of Stabilized Fuzzy Relation-based Neural Networks Driven To Ensemble Neurons/layers and Multi-optimization)

摘要

By a News Reporter-Staff News Editor at Network Daily News - Investigators publish new report on Networks. According to news reporting originating in Gyeonggi-do, South Korea, by NewsRx journalists, research stated, “In this study, a design methodology based on fuzzy relation-based neural networks for stabilized network structure is introduced to cope with over-fitting as well as multicollinearity problems which generally appear in conventional fuzzy neural networks. The design method of the proposed self-organizing network structure provides an efficient solution to construct the stabilized Fuzzy Relation-based Neural Networks (FRNN) through a synergy of multi-techniques such as ensemble neurons/layers, L2-norm regularization, compromise technique, and multi-optimization, in order to generate the structure of the multi-layered self-organizing network designed with the aid of the learning as well as novel structural design.The overall network structure is realized with the aid of parallel network structure with newly added layers as well as effective node selection method through the combination technique of both a sum of squared coefficients (SSC) and performance index (PI) as a node selection criterion for each layer in FRNN.”