inverse dynamic model neural network
Hybrid Neural Network Controller Design for a Batch Reactor to Produce Methyl Methacrylate
... problem, neural networks studied and provided successfully to capture the dynamics of nonlinear and complex systems have been proposed and formulated ...[8-13]. Neural networks have several advantages of ...
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Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network
... Because of low voltage and high current output characteristic of the fuel cell generation system, the system performance is very sensitive to load variations, so the control system should compensate this by making the ...
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Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
... to model the complex systems (Wanous et al, ...the inverse transformation of obtained fuzzy numbers to the numerical data in the real-world (Tsipouras et al, ...
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NEURO MODELING AND CONTROL STRATEGIES FOR A pH PROCESS
... the dynamic behavior of such systems using conventional modeling techniques thereby designing controller ...a neural network based internal model control is designed for a pH process and its ...
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Web Text Classification Using Genetic Algorithm and a Dynamic Neural Network Model
... Web text classification problems are characterized by high dimensionality and are highly complex in nature. In order to reduce complexity, some preprocessing techniques are applied to the original text to make it into a ...
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Implementation of neural network based inverse model control strategies on an exothermic reactor
... and dynamic behaviour, such as ignition/extinction behaviour and parametric sensitivity create challenges that are tough for traditional linear controllers to ...based inverse-model control ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... a dynamic optimization strategy is applied to determine an acetone distillate composition profile maximizing the weight of the distillate product ...of neural network model-based controllers: ...
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Behavioral Modeling of RF Power Amplifiers with Memory Effects Using Orthonormal Hermite Polynomial Basis Neural Network
... real-valued neural networks were used to model the output amplitude and phase (or the output I and Q components) with the input signal amplitude as the two neural networks’ input, as shown in Figure ...
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A Data Mining Model by Using ANN for Predicting Real Estate Market: Comparative Study
... Neural network is an artificial intelligence model origin- nally designed to replicate the human brain’s learning ...The model consists of three main layers: input data layer (example the ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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Inverse P data Models and Data Intelligent Separation
... on inverse P-set as follows: by improving in- verse P-set, inverse P-data models and inverse P-data reasoning are proposed, appli- cations of data intelligent separation-discovery are ...given. ...
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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
... this network can be mapped into a state-space equation, so the determining the network structure is equivalent to finding system ...space model form. Subspace algorithms estimate the state-space ...
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Design of Low Noise Amplifier of IRNSS using ANN
... artificial neural networks (ANNs). In the last two decades artificial neural networks have found their place as an efficient tool for modeling of microwave devices [2, ...ANN model is developed to ...
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Dynamic Entity Representations in Neural Language Models
... memory block specifically to only one entity. Entity-related models. Two recent approaches to modeling entities in text are closely related to our model. The first is the “reference-aware” lan- guage models ...
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Application of PSO BP Neural Network Model on Identification of Human Dynamic Balance
... The dynamic balance ability of human body is an ability that human body carries out an action actively (walking, running, jumping) or as well as suffers interference stimuli (Impact, stumble, visual stimulation) ...
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BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... Grey neural network model is denoted by GNNM(h, n), wherein, h is the order of the differential equations, n is the number of sequences involved in the ...Grey neural network ...
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Applying Neural Network Architecture for Inverse Kinematics Problem in Robotics
... In inverse kinematics learning, the complexity is in the geometric and non linear equations (trigonometric equa- tions) and in the matrix inversion, this in addition to some other difficulties faced in ...
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Geoscientific Model Development
... We validated both neural networks with completely indepen- dent data using a selection of actual satellite ephemerides. These ephemerides and solar wind conditions where not part of the training data set. The ...
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Neural Network PID Algorithm for a Class of Discrete-Time Nonlinear Systems
... system model has gradually become an im- portant topic in control ...the neural network control, fuzzy logic control, the sliding mode con- trol and model free adaptive control ...
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Span Based Constituency Parsing with a Structure Label System and Provably Optimal Dynamic Oracles
... our dynamic oracle can be computed in amortized constant time since there are only O(n) gold brackets and thus bounding | reach(c) | and the choice of ...our dynamic oracle is much faster than the ...
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