Journal ArticleDOI
Identification using ANFIS with intelligent hybrid stable learning algorithm approaches and stability analysis of training methods
Mahdi Aliyari Shoorehdeli,Mohammad Teshnehlab,Ali Khaki Sedigh,M. Ahmadieh Khanesar +3 more
- Vol. 9, Iss: 2, pp 833-850
TLDR
It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints and stable learning algorithms for two common methods are proposed based on Lyapunov stability theory and some constraints are obtained.Abstract:
This paper proposes a novel hybrid learning algorithm with stable learning laws for Adaptive Network based Fuzzy Inference System (ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on particle swarm optimization (PSO) for training the antecedent part and forgetting factor recursive least square (FFRLS) for training the conclusion part. Two famous training algorithms for ANFIS are the gradient descent (GD) to update antecedent part parameters and using GD or recursive least square (RLS) to update conclusion part parameters. Lyapunov stability theory is used to study the stability of the proposed algorithms. This paper, also studies the stability of PSO as an optimizer in training the identifier. Stable learning algorithms for the antecedent and consequent parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given to validate the results. It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints. The learning rate can be calculated on-line and will provide an adaptive learning rate for the ANFIS structure. This new learning scheme employs adaptive learning rate that is determined by input-output data. Also, stable learning algorithms for two common methods are proposed based on Lyapunov stability theory and some constraints are obtained.read more
Citations
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Journal ArticleDOI
Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey
Dervis Karaboga,Ebubekir Kaya +1 more
TL;DR: The heuristic and hybrid approaches utilized in ANFIS training are examined in order to guide researchers in their study and it has been observed that there is a trend toward heuristic based ANfIS training algorithms for better performance recently.
Journal ArticleDOI
Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Wind Power Forecasting in Portugal
TL;DR: A novel hybrid approach, combining wavelet transform, particle swarm optimization, and an adaptive-network-based fuzzy inference system, is proposed in this paper for short-term wind power forecasting in Portugal.
Journal ArticleDOI
Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting
TL;DR: In this article, a hybrid approach combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system is proposed for short-term electricity prices forecasting in a competitive market.
Journal ArticleDOI
Recent advances in neuro-fuzzy system: A survey
K V Shihabudheen,G. N. Pillai +1 more
TL;DR: A review of different neuro-fuzzy systems based on the classification of research articles from 2000 to 2017 is proposed to help readers have a general overview of the state-of-the-arts of neuro- fizzy systems and easily refer suitable methods according to their research interests.
Journal ArticleDOI
Adaptive intelligent energy management system of plug-in hybrid electric vehicle
TL;DR: The proposed adaptive intelligent energy management system can learn while it is running and makes proper adjustments during its operation and it is shown that the proposed intelligentEnergy management system is improving the performance of other existing systems.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Journal ArticleDOI
ANFIS: adaptive-network-based fuzzy inference system
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Journal ArticleDOI
Identification and control of dynamical systems using neural networks
TL;DR: It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems and the models introduced are practically feasible.