TY - CHAP
T1 - Deep neuro-fuzzy architectures
AU - Dorzhigulov, Anuar
AU - James Pappachen, Alex
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Fuzzy logic inspires from the non-deterministic behaviour of human brain computations. The fusion of neural networks and fuzzy logic such as neuro-fuzzy architectures is natural, as both represent elementary inspiration from brain computations involving learning, adaptation and ability to tolerate noise. This chapter focuses on neuro-fuzzy and alike solutions for machine learning from perspective of functionality, architectures and applications.
AB - Fuzzy logic inspires from the non-deterministic behaviour of human brain computations. The fusion of neural networks and fuzzy logic such as neuro-fuzzy architectures is natural, as both represent elementary inspiration from brain computations involving learning, adaptation and ability to tolerate noise. This chapter focuses on neuro-fuzzy and alike solutions for machine learning from perspective of functionality, architectures and applications.
UR - http://www.scopus.com/inward/record.url?scp=85064762401&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064762401&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-14524-8_15
DO - 10.1007/978-3-030-14524-8_15
M3 - Chapter
AN - SCOPUS:85064762401
T3 - Modeling and Optimization in Science and Technologies
SP - 195
EP - 213
BT - Modeling and Optimization in Science and Technologies
PB - Springer Verlag
ER -