Home / Current Issue / Paper 1700648
Neural Networks: Nervous System Of Digital World
Subject area: Science,Engineering and Technology · Area of research: ELECTRONICS AND COMMUNICATION ENGINEERING
Abstract
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.
Keywords
Neural Networks; Fuzzy Logics; Artificial Intelligence; Machine Learning;
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How to cite this paper
@article{1700648,
author = {Preeti Rawat},
title = {Neural Networks: Nervous System Of Digital World},
journal = {Iconic Research And Engineering Journals},
year = {2018},
volume = {1},
number = {10},
pages = {154-157},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1700648.pdf},
abstract = {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.},
keywords = {Neural Networks; Fuzzy Logics; Artificial Intelligence; Machine Learning;},
month = {April},
}