Expert Systems with Applications: An International Journal
Journal of Computational and Applied Mathematics
Computers in Biology and Medicine
Adaptive controller with fuzzy rules emulated structure and its applications
Engineering Applications of Artificial Intelligence
Review: Development of soft computing and applications in agricultural and biological engineering
Computers and Electronics in Agriculture
An application of neuro-fuzzy technology for analysis of the CO2 capture process
Fuzzy Sets and Systems
A neural-fuzzy modelling framework based on granular computing: Concepts and applications
Fuzzy Sets and Systems
A recurrent neuro-fuzzy system and its application in inferential sensing
Applied Soft Computing
Modeling of the carbon dioxide capture process system using machine intelligence approaches
Engineering Applications of Artificial Intelligence
Soft computing methods applied to train station parking in urban rail transit
Applied Soft Computing
Computers and Electronics in Agriculture
Rule-base derivation for intensive care ventilator control using ANFIS
Artificial Intelligence in Medicine
Estimation of heart rate signals for mental stress assessment using neuro fuzzy technique
Applied Soft Computing
Evaluating direction-of-change forecasting: Neurofuzzy models vs. neural networks
Mathematical and Computer Modelling: An International Journal
Relation-based neurofuzzy networks with evolutionary data granulation
Mathematical and Computer Modelling: An International Journal
Hierarchical neuro-fuzzy call admission controller for ATM networks
Computer Communications
SoHyFIS-Yager: A self-organizing Yager based Hybrid neural Fuzzy Inference System
Expert Systems with Applications: An International Journal
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
Performance divergence with data discrepancy: a review
Artificial Intelligence Review
Hi-index | 0.01 |
A fuzzy modeling method using fuzzy neural networks with the backpropagation algorithm is presented. The method can identify the fuzzy model of a nonlinear system automatically. The feasibility of the method is examined using simple numerical data