neural-network-based fuzzy control
Control of Nonlinear Industrial Processes Using Fuzzy Wavelet Neural Network Based on Genetic Algorithm
... of fuzzy rules and to purify the wavelets for each ...proposed control scheme the error between desired system output and output of control object is directly utilized to tune the network ...
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Control Performance Standard based Load Frequency Control of a two area Reheat Interconnected Power System considering Governor Dead Band nonlinearity using Fuzzy Neural Network
... Elman network is a typical dynamic recurrent neural network whose feedback consists of a group of connected modules and is used to record the implicit ...the network input, acts as the import ...
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Fuzzy Logic Genetic Algorithm Neural Network for Mobile Robot Navigation: A Survey
... equation. Neural predictive control scheme is presented in [110] for car like mobile ...model based predictive ...forward neural networks. In [111], a neural dynamic based ...
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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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Application of Fuzzy PID Adaptive Algorithm Based on RBF Network in Smart Car
... speed control system is a nonlinear time varying systems, to establish a precise mathematical model isn’t easy, using conventional PID control is not very ...RBF neural network with ...
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Online Full Text
... the network connectivity active to meet the applications/users ...the network stability and QoS ...admission control(CAC) algorithms proposed in the literature to handle single-class network ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... of fuzzy logic and neural networks, a better understanding of the heuristics underlying the motor fault de- tection/diagnosis process and successful fault detection/diagnosis schemes can be ...two ...
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Direct torque control of three phase induction motor using neural network fuzzy logic techniques
... of control and estimation of ac drives arises due to dynamics of ac machines, variation in machine parameter and processing of feedback signals in presence of ...Oriented Control (FOC) is widely used in ...
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On hybrid intelligence-based control approach with its application to flexible robot system
... as control, electronics, computer, mechanics and ...the fuzzy-based concepts can be discussed in the area of control systems of smart ...The neural network is used to design the ...
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Vol 2, No 11 (2014)
... Speed Control of Induction motor can be obtained by maximum torque and ...the neural networks, improves the performance & operation of induction motor ...conventional, Fuzzy and Neural ...
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Hybrid Neural Network Controller Design for a Batch Reactor to Produce Methyl Methacrylate
... temperature control. This work presents a neural network forward model (NN) to predict a concentration of methyl methacrylate, a jacket temperature and temperature profile in the ...predictive ...
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Design of radial basis function neural network controller for BLDC motor control system
... RBF neural network are phase current and speed, output signal is duty cycle D, the input and output are applied in BLDC motor control system, it can change control parameters on-line and ...
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Performance analysis of neural network based control of hypnosis and analgesia during anesthesia by employing a pharmacokinetic pharmacodynamic model
... Model Control (IMC) philosophy relies on the Internal Model Principle, which states that control can be achieved only if the control system encapsulates, either implicitly or explicitly, some ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... smooth control movement (reflux ratio) as shown in ...the neural network model used in the NNMPC is trained covering the possible parametric plant uncertainties as described in the section ...minimum ...
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FAIR: A Fuzzy ART Network Based Scheme for Retrieving Useful Information from Blogs
... a Fuzzy Adaptive Resonance Theory (ART) network [2] based Information Retrieval (FAIR) scheme by integrating Fuzzy ART, Latent Semantic Indexing (LSI) [6], and association rules discovery [9], ...
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A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction
... the neural-based models, 20 simulations are conducted, and the averaged results are collected for comparison ...functional neural network (RBFNN), and an adaptive neuro-fuzzy inference ...
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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process
... 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
... as neural network models, in modeling and forecasting the market indexes can yield impressive results (Aladag et ...as neural network models, is a response to the lack of consensus on ...
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Modelling the formation of Ozone in the air by using Adaptive Neuro-Fuzzy Inference System (ANFIS) (Case study: city of Yazd, Iran)
... data based on previous assumed ...is fuzzy logic: to use this method the data should be sorted by clustering algorithm based on iterative optimization (Morabito and Versaci, ...
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Neuro fuzzy Modeling of an Eco friendly Melting Furnace Parameters using Bio fuels for the Agile Production of Quality Castings
... extracting fuzzy knowledge from numerical data and linguistic data into the ...applying fuzzy logic for systems represented by numerical knowledge (data sets), or in applying neural networks for ...
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