Modeling renewable energy systems by a self-evolving nonlinear consequent part recurrent type-2 fuzzy system for power prediction
A novel Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) is
presented for the modeling of renewable energy systems. Not only does this paper present a …
presented for the modeling of renewable energy systems. Not only does this paper present a …
NeuroQuMan: Quantum neural network-based consumer reaction time demand response predictive management
A Safari, MA Badamchizadeh - Neural Computing and Applications, 2024 - Springer
Demand response, and artificial intelligence integration with it, have a considerable effect in
optimizing energy consumption, grid stability, and promoting sustainable energy practices …
optimizing energy consumption, grid stability, and promoting sustainable energy practices …
Interval type-2 fuzzy neural networks with asymmetric MFs based on the twice optimization algorithm for nonlinear system identification
J Liu, T Zhao, J Cao, P Li - Information Sciences, 2023 - Elsevier
This paper proposes a novel algorithm twice optimization for interval type-2 fuzzy neural
networks with asymmetric membership functions (TOIT2FNN-AMF), for nonlinear system …
networks with asymmetric membership functions (TOIT2FNN-AMF), for nonlinear system …
Nonlinear system identification based on a self-organizing type-2 fuzzy RBFN
This paper presents a new self-evolving recurrent Type-2 Fuzzy Radial Basis Function
Network (T2FRBFN) in which the weights are considered Gaussian type-2 fuzzy sets and …
Network (T2FRBFN) in which the weights are considered Gaussian type-2 fuzzy sets and …
A meta-cognitive interval type-2 fuzzy inference system and its projection based learning algorithm
A meta-cognitive interval type-2 neuro-fuzzy inference system (McIT2FIS) based classifier
and its projection based learning algorithm is presented in this paper. McIT2FIS consists of …
and its projection based learning algorithm is presented in this paper. McIT2FIS consists of …
Stable ANFIS2 for nonlinear system identification
This paper presents a novel adaptive neuro fuzzy inference system that uses interval
Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as …
Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as …
A new type-II fuzzy system for flexible-joint robot arm control
J Tavoosi, F Mohammadi - 2019 6th International Conference …, 2019 - ieeexplore.ieee.org
In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on the Interval
Gaussian Type-II Fuzzy sets in the antecedent part and Gaussian Type-I Fuzzy sets as …
Gaussian Type-II Fuzzy sets in the antecedent part and Gaussian Type-I Fuzzy sets as …
Backstepping-based recurrent type-2 fuzzy sliding mode control for MIMO systems (MEMS triaxial gyroscope case study)
This paper presents a novel type-2 fuzzy sliding mode control with nonlinear consequent
part in fuzzy rules for control of Micro-Electro-Mechanical Systems (MEMS) gyroscope. The …
part in fuzzy rules for control of Micro-Electro-Mechanical Systems (MEMS) gyroscope. The …
PMSM speed control based on intelligent sliding mode technique
J Tavoosi - COMPEL-The international journal for computation and …, 2020 - emerald.com
Purpose The purpose of this paper is to present a novel intelligent backstepping sliding
mode control for an experimental permanent magnet synchronous motor …
mode control for an experimental permanent magnet synchronous motor …
Stability analysis of recurrent type-2 TSK fuzzy systems with nonlinear consequent part
A necessary condition for stability of a class of recurrent type-2 TSK fuzzy systems is
presented. In this system, the antecedent part is indeed represented by interval Gaussian …
presented. In this system, the antecedent part is indeed represented by interval Gaussian …