JOURNAL ARTICLE
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
Krzysztof CpałkaKrystian ŁapaAndrzej PrzybyłMarcin Zalasiński
Year: 2014 Journal: Neurocomputing Vol: 135 Pages: 203-217 Publisher: Elsevier BV
Keywords:
Interpretability Computer science Predictability Machine learning Artificial intelligence Neuro-fuzzy Identification (biology) Fuzzy logic Selection (genetic algorithm) Nonlinear system Interpretation (philosophy) Fuzzy control system Data mining Mathematics
Metrics
85
Cited By
28.01
FWCI (Field Weighted Citation Impact)
68
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Citation History
Topics
Fuzzy Logic and Control Systems
Physical Sciences → Computer Science → Artificial Intelligence
Neural Networks and Applications
Physical Sciences → Computer Science → Artificial Intelligence
Evolutionary Algorithms and Applications
Physical Sciences → Computer Science → Artificial Intelligence
Related Documents
BOOK-CHAPTER
On Designing of Flexible Neuro-Fuzzy Systems for Nonlinear Modelling
Krzysztof CpałkaO. Yu. RebrovaRobert NowickiLeszek Rutkowski
Lecture notes in computer science Year: 2011 Pages: 147-154
BOOK-CHAPTER
A New Method for Designing and Complexity Reduction of Neuro-fuzzy Systems for Nonlinear Modelling
Krystian ŁapaMarcin ZalasińskiKrzysztof Cpałka
Lecture notes in computer science Year: 2013 Pages: 329-344
BOOK-CHAPTER
A New Interpretability Criteria for Neuro-Fuzzy Systems for Nonlinear Classification
Krystian ŁapaKrzysztof CpałkaA.I. Galushkin
Lecture notes in computer science Year: 2015 Pages: 448-468
JOURNAL ARTICLE
Interpretability and learning in neuro-fuzzy systems
Rui Pedro PaivaAntónio Dourado
Journal: Fuzzy Sets and Systems Year: 2003 Vol: 147 (1)Pages: 17-38
BOOK-CHAPTER
New Aspects of Interpretability of Fuzzy Systems for Nonlinear Modeling
Krystian ŁapaKrzysztof CpałkaLeszek Rutkowski
Studies in computational intelligence Year: 2017 Pages: 225-264