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fuzzy neural network structure

Electricity Price Forecasting using Asymmetric Fuzzy Neural Network Systems

Electricity Price Forecasting using Asymmetric Fuzzy Neural Network Systems

... Gaussian Fuzzy Inference Neural Network (AGFINN), utilizing a Takagi–Sugeno–Kang (TSK) structure, has been considered as an identification model for electricity price ...of fuzzy rules, ...

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II. NTERVAL TYPE

II. NTERVAL TYPE

... type-2 fuzzy neural network with asymmetric membership functions ...type-2 fuzzy sets and it implements the fuzzy logic system (FLS) in a five-layer neural network ...

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An Efficient Method for Selecting the Optimal Structure of a Fuzzy Neural Network Architecture

An Efficient Method for Selecting the Optimal Structure of a Fuzzy Neural Network Architecture

... artificial neural networks with soft computing enables to construct learning ma- chines that are superior compared to classical artificial neural networks because knowledge can be extracted and explained in ...

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Online Full Text

Online Full Text

... using neural networks is an upcoming approach in pattern ...Reflex Fuzzy Min-Max Neural Network ...the structure of human nervous system, GrRFMN architecture is consisting of a reflex ...

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The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models

The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models

... the network adjusting at a certain level the fuzzy system remains without any ...specific fuzzy system ...neuro fuzzy systems can be classified into four types: 1-The cooperative ...

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Adaptive Neuro-Fuzzy Systems

Adaptive Neuro-Fuzzy Systems

... of fuzzy model, two different phases must be carried out in fuzzy modeling, designated as structural and parametric ...the structure of the rules, i.e. the number of rules and the number of ...

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A Hybrid Edge Detection Algorithm for Salt- and-Pepper Noise

A Hybrid Edge Detection Algorithm for Salt- and-Pepper Noise

... The structure of our proposed edge detector, to make the process robust against noise, is a combination of neural networks, neuro-fuzzy network and adaptive median ...

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COMPARING EVOLUTIONARY ALGORITHMS ON TUNING THE PARAMETERS OF FUZZY WAVELET NEURAL NETWORK

COMPARING EVOLUTIONARY ALGORITHMS ON TUNING THE PARAMETERS OF FUZZY WAVELET NEURAL NETWORK

... the structure of the FWNN model was introduced for function approximation from input– output ...of fuzzy concepts, wavelet functions, and neural ...

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Evolving Intelligent Systems, eIS

Evolving Intelligent Systems, eIS

... a neural network which is not trained; they learn new rules (develop the links of their neural network) during their life from experience based on the data streams that their preceptors ...

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A New Neural Network Structure: Node to Node Link Neural Network

A New Neural Network Structure: Node to Node Link Neural Network

... the network pa- rameters based on the gradient information of the cost ...are network structure depend- ...Recently, neural or neural-fuzzy networks train- ed with RCGA are ...

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Auto control of pumping operations in sewerage systems by rule based fuzzy neural networks

Auto control of pumping operations in sewerage systems by rule based fuzzy neural networks

... counterpropagation network (CPN), which was pro- posed by Hecht-Nielsen (1987), functions as a self- programming optimal lookup table, providing the mapping between input and output ...and fuzzy arithmetic, ...

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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process

Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process

... similar structure to a multilayer feed forward neural network, but the links in an ANFIS only indicate the flow direction of signals between nodes and no weights is associated with the ...

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Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange

Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange

... artificial neural networks has many considerable advantages; first, neural networks have a high similarity with the human nervous system, and unlike the traditional methods, they are data-driven ...

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Review Computer Network Routing with a Fuzzy Neural Network

Review Computer Network Routing with a Fuzzy Neural Network

... in network technologies and management techniques so users will receive high quality ...computer network, the quality of service received by the users begins to ...computer network can assist with ...

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A Technical Review on Intrusion Detection System

A Technical Review on Intrusion Detection System

... like Neural Network, Support Vector Machine, Genetic algorithm, Clustering, Fuzzy Logic can be used to implement ...sized network which catches the standard ...diverse network, but it ...

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Artificial Intelligence and its Application as an Integrated Approach

Artificial Intelligence and its Application as an Integrated Approach

... The human brain is composed of 86 billion nerve cells called neurons. They are connected to other thousand cells by Axons. Stimuli from external environment or inputs from sensory organs are accepted by dendrites. These ...

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Fuzzy Neural Network for Clustering and Classification

Fuzzy Neural Network for Clustering and Classification

... a fuzzy neural network for clustering and ...this fuzzy neural network two training algorithm are implemented for clustering and ...General Fuzzy min max Neural ...

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Neural Network Regressions with Fuzzy Clustering

Neural Network Regressions with Fuzzy Clustering

... hybrid neural network regression models with unsupervised fuzzy clustering is proposed for clustering nonparametric regression models for ...the neural network regression models is ...

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Online Full Text

Online Full Text

... TSK-type fuzzy network control (ATFNC) system for synchronization of a coupled nonlinear chaotic ...a neural controller and a fuzzy compensator. The neural controller uses a ...

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Sentiment Analysis Using Hybrid Machine Learning Technique

Sentiment Analysis Using Hybrid Machine Learning Technique

... Also some reviews neither belong to positive cluster nor to negative. They mixed reaction or feeling about some topics. Those problem associated with NLP is solved using hybrid technique of the fuzzy c-means and ...

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