Whilst neurofuzzy systems have become an attractive powerful data modelling technique, combining well established learning laws of neural networks and the linguistic transparency of fuzzy logic, they do suffer from the curse of dimensionality. A network with two inputs with seven fuzzy sets per input...
Finally, nonlinear fuzzy activation functions are used to aggregate all the local models to capture the overall system behaviour. The NF technique has been shown to be highly promising not only in the area of nonlinear dynamic systems modelling, but also in various other application areas, such ...
Neuro-fuzzy modelling A fuzzy inference system is a model that takes a fuzzy set as an input and performs a composition to arrive at the output based on the concepts of fuzzy set theory, fuzzy if-then rules and fuzzy reasoning [4]. Simply put, the Fuzzy inference procedure involves:...
Neurofuzzy Modelling Approaches in System Identification System identification is the task of constructing representative models of processes and has become an invaluable tool in many different areas of science a... KM Bossley 被引量: 112发表: 1997年 Modelling of nonlinear dynamical systems using supp...
FUZZY logicAUTOREGRESSIVE modelsELECTRIC wheelchairsTwo-wheeled wheelchairs have been used as alternatives for the elderly and disabled people to perform physical activities due to their restriction of movement. Significant challenges posed by two-wheeled wheelchairs control due to their...
ParsimoniousNeurofuzzyModellingK.M.Bossley,M.Brown,andC.J.HarrisIntroductionModellinghasbecomeaninvaluabletoolinmanyar-easofresearch,particu..
In this research an adaptive neuro-fuzzy inference system (ANFIS) has been applied to study the effect of working conditions on occupational injury using d... NG Fragiadakis,VD Tsoukalas,VJ Papazoglou - 《Safety Science》 被引量: 23发表: 2014年 Neuro‐fuzzy modelling of spectroscopic data. Pa...
Fuzzy modelling and ANFIS: Adaptive neuro-fuzzy inference system Fuzzy inference is a method that interprets the values in the input vector and assigns values to the output by means of some set of fuzzy “IF-THEN” rulesIFxisATHENyisB,where A and B are labels of fuzzy sets, e.g, “low...
Control Of An Electro-Hydraulic System Using Neuro-Fuzzy Modelling And Real-Time Learning Approaches 来自 ResearchGate 喜欢 0 阅读量: 24 作者:PJC Branco,JA Dente 摘要: Drive systems are fundamental parts of industrial processes. Although, their conventional models and projected controllers based on ...
Moreover, a comparative analysis between the artificial neural networks (ANNs) and adaptive neuro-fuzzy inference (ANFIS) models by exploring their modelling capabilities regarding the mathematical structures and identification algorithms in providing an accurate and computational effective behavioral model for...