Parameters of Neural Network
Comparative Study of Neural Network based RSA Cryptosystem on Various Parameters
... Artificial neural networks are composed of neurons which are the fastest processing ...artificial neural network. The network used here for implementation of RSA is multilayer feed forward ...
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Prediction and Optimization of Blast Furnace Parameters using Artificial Neural Network
... Artificial Neural Network ...these parameters in ...input parameters used are Oxygen enrichment, Blast volume, Blast pressure, Top gas pressure, Hot Blast temperature, steam injection rate, ...
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Conjugate gradient neural network in prediction of clay behavior and parameters sensitivities
... artificial neural network method has yet to be ...by neural network ...artificial neural network method is based on the data alone in which the model can be trained on ...
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CALCULATION OF MICROSTRIP PATCH ANTENNA PARAMETERS USING ARTIFICIAL NEURAL NETWORK.
... Artificial Neural Network for solution of different Parameters of Microstrip Patch ...Artificial Neural Network has been used because it provides a higher degree of interconnections of ...
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Artificial Neural Network Modelling for Polyethylene FSSW Parameters
... FSSW parameters (welding stirring time, plunge depth, and tool rotational speed) and lap-shear fracture load of HDPE welds are shown in Figures 1, 2, and 3, ...welding parameters. The eects of welding ...
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Wavelet Neural Network with Random Wavelet Function Parameters
... Neural Network with Random Weights (NNRWs) is another topic related to the present ...layer network, where the input weights and biases are assigned randomly, and the output weights are calculated ...
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Optimization of EDM Process Parameters by Using Artificial Neural Network: A Review
... Optimization of the machining process using a GA-based neural network. It was observed that GA has sufficient prediction and reasoning capability to generate optimal process parameters. The process ...
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Optimization of underwater wet welding process parameters using neural network
... artificial neural network (ANN) which is capable of solving difficult and complex ...the neural network control of the input parameters as shown in Figure ...process parameters ...
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Neural Network Prediction Parameters Quality Of Electrical Energy
... regression network was chosen as the neural network, which realizes methods of nuclear ...the network output can be considered as the expected value of the model at a given point in the input ...
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COMPARING EVOLUTIONARY ALGORITHMS ON TUNING THE PARAMETERS OF FUZZY WAVELET NEURAL NETWORK
... Abstract– In recent years Fuzzy Wavelet Neural Networks (FWNNs) have been used in many areas. Function approximation is an important application of FWNNs. One of the main problems in effective usage of FWNN is ...
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Comparison of Neural Network Parameters for Classification of Arabic Handwritten Isolated Characters
... a neural network, it is not enough to evaluate the convergence of its quadratic errors, but also the recognition rate and the execution ...all neural networks tested with normalized data was in the ...
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1. Kernel network parameters optimization using optimized artificial neural network to serve quality of service parameters
... computer network centric operations when data volumes and near real-time data processing requirements is very ...performance network is benefited a ...computing network require support of very big ...
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Non linear algorithm analysis of large scale traffic data for systematic pattern detection
... artificial neural networks have been widely used for estimating traffic parameters and it can be conclude that Artificial Neural Network (ANN) technique may be used to estimating missing data ...
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Shape Optimization of Pedestals Using Artificial Neural Network
... the neural network. For this a 2-3-1 size, back propagation neural network is ...input parameters are stress and ‘X’ and output parameter ís ...trained network is used for ...
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Neural Network Toolbox for MATLAB - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... the network are engine speed and fueling levels and the network outputs are torque and emission ...The network used for this problem is a 2-30-2 network with tansig neurons in the hidden layer ...
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Short Term Load Forecasting With Feed Forward Neural Network Algorithm
... the network can learn dependencies on them that do not really exist in the real ...free parameters in the model, the more likely the over fitting ...free parameters in the model, so in order to avoid ...
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Evolving binary-weights neural network using hybrid optimization algorithm for color space conversion
... An individual or solution to the problem to be solved is represented by a list of parameters called chromosome or genome. Genes and chromosomes are the basic building blocks of the GA. The conventional standard GA ...
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Using Neural Networks to Follow the Wear of a S390 Twist Drill
... of neural networks for the information integration of the cutting-process parameters, the drill-sharpening method and the operation time in relation to the tool-wear parameters is treated in this ...
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Effective Prediction of Thermal Conductivity of Concrete Using Neural Network Method
... back-propagation neural network models on the basis of experimental values carried out by previous researchers have been utilized to effectively account for the influence of these ...The neural ...
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RSI RANGE DETERMINATION USING CUBICAL DISTANCE CLASSIFICATION
... the network, and other sets of data are used to test the ...the neural network, adjustment of weights and parameters, network file creation and finally testing of the field data for the ...
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