Neuro-fluffy hybridization brings about a mixture insightful framework that synergizes these two procedures by consolidating the human-like thinking style of fluffy frameworks with the learning and connectionist structure of neural systems. Neuro-fluffy hybridization is generally named as fluffy neural system (FNN) or neuro-fluffy framework (NFS) in the writing. Neuro-fluffy framework (the more prevalent term is utilized hereafter) consolidates the human-like thinking style of fluffy frameworks using fluffy sets and a semantic model comprising of an arrangement of IF-THEN fluffy principles. The primary quality of neuro-fluffy frameworks is that they are all inclusive approximators with the capacity to request interpretable IF-THEN guidelines. The quality of neuro-fluffy frameworks includes two conflicting necessities in fluffy demonstrating: interpretability versus precision. Practically speaking, one of the two properties wins. The neuro-fluffy in fluffy demonstrating research field is isolated into two regions: phonetic fluffy displaying that is centered around interpretability, mostly the Mamdani show; and exact fluffy displaying that is centered around exactness, predominantly the Takagi-Sugeno-Kang (TSK) show.
Neural Networks; Fuzzy Logics; Artificial Intelligence; Machine Learning;
Preeti Rawat "Neural Networks: Nervous System Of Digital World" Iconic Research And Engineering Journals Volume 1 Issue 10 2018 Page 154-157
Preeti Rawat "Neural Networks: Nervous System Of Digital World" Iconic Research And Engineering Journals, 1(10)