[PDF] Top 20 Performance Enhancement of RSA Algorithm Using Artificial Neural Networks
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Performance Enhancement of RSA Algorithm Using Artificial Neural Networks
... A neural network is a machine that is designed to model the way in which the brain performs a particular ...by using electronic components or is simulated in software on a digital ...A neural network ... See full document
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Approaches in RSA Cryptosystem Using Artificial Neural Network
... Backpropagation) Neural network against the RSA cryptosystem were employed and from the illustrated results it is clear that though the RB neural network is very good at function estimation, in the ... See full document
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A Theoretical Framework for Property Enhancement of Smart Materials Based on Manufacturing Process Modeling Using Artificial Neural Networks.
... The amount of training data required is contingent on many factors of the cumulative manufacturing process. The volume of training data is critical to estimating the number of records to be imported from an experimental ... See full document
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THE TRANSITION FROM 4G TO 5G BY EMPLOYING FEMTO CELLS PROVEN THROUGH DATA RATE, PLR AND DELAY
... of artificial intelligence are expert systems, neural networks, fuzzy logic and genetic algorithms ...So, neural networks were used in this work which is considered the most powerful ... See full document
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Experimental Investigation of Classification Algorithms for Predicting Lesion Type on Breast DCE MR Images
... as artificial neural networks, support vector machines and artificial bee colony optimization algorithm trained neural ...selection using the statistical hypothesis t-test ... See full document
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Detecting and classifying diabetic retinopathy in fundus retina images using artificial neural networks based firefly clustering algorithm
... Future studies, focusing on larger samples and prospective clinical trials, are needed for further validation. The present method, tested on artificially and naturally-degraded retinal images, obtained an important ... See full document
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Vector Control of a Grid-Connected Rectifier/Inverter Using an Artificial Neural Network
... problems using a neural network to control a grid-connected ...The neural network implements a dynamic programming (DP) algorithm and is trained using backpropagation through ...The ... See full document
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Prediction of agricultural tractor noise levels using artificial neural networks
... user. Networks with biases, a sigmoid layer, and a linear output layer are capable of approximating any function with a finite number of ...descent algorithm, as is the Widrow-Hoff learning rule, in which ... See full document
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Research on Classification of E-shopper Based on Neural Networks and Genetic Algorithm
... optimal algorithm of modeling dynamic architecture for artificial neural networks (ANN) and a novel machine-learning algorithm for extracting rules from databases via using ... See full document
8
Bearing Fault Detection Using Artificial Neural Networks and Genetic Algorithm
... the performance of bearing fault detection using three types of artificial neural networks (ANNs), namely, multilayer perceptron (MLP), radial basis function (RBF) network, and ... See full document
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Artificial Neural Network Learning Enhancement using Bacterial Foraging Optimization Algorithm
... optimizing algorithm, which attempts to reduce the error in the network output by adjusting the matrix of network ...Optimization Algorithm is utilized to solve optimization related problems ...of ... See full document
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Accuracy Enhancement of Artificial Neural Network using Genetic Algorithm
... genetic algorithm and neural network. Multilayered feed forward neural networks are used to classify the complex ...the neural network are driven using genetic algorithm ... See full document
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PREDICTION OF PERFORMANCE AND EMISSIONS OFCI ENGINE FUELLED WITH SUNFLOWER OIL AND ITS BLENDS WITH DIESEL USING ARTIFICIAL NEURAL NETWORK
... predict performance and emissions with BPNN algorithm and good correlation coefficient was ...various performance and emission parameters like torque, bsfc, brake thermal efficiency and reported that ... See full document
14
System health management of safety critical systems using artificial neural networks
... basic neural network tool boxes that are ...for artificial neural ...for artificial neural networks in deep learning ...of neural network system for one who coming from ... See full document
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Improving robustness of artificial neural networks model using genetic algorithm
... In this work, an ANN model is used for inferential estimation of product composition in a distillation column. The ain is to address an issue in process industries, i.e.[r] ... See full document
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Performance prediction of a thermal system using Artificial Neural Networks
... Condenser‟s performance will degrade with the time from design to real ...condenser performance, which is responsive for changes in the FF across the heat transfer ... See full document
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The Influence of Composite Laminate Stacking Sequence on Failure Load of Bonding Joints Using Experimental and Artificial Neural Networks Methods
... Failure load prediction of single lap adhesive joints using artificial neural networks. Aydın, An artificial neural network model for predicting compression strength of heat [r] ... See full document
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Prediction of CEC using fractal parameters by artificial neural networks
... In this study, firstly, we extend the entire PSD curve from limited soil texture data and obtained PSD curve model (the model of Skaggs et al. (2001)) parameters. At the second step, the fractal model of Bird et al. ... See full document
10
Analysis of Software Performance Enhancement and Development of Algorithm
... When a programmer has a solid knowledge of a programming language used for automation issues, he/she can easily manage on the other knowledge. Moreover, a programmer understands the structure of the program more easily ... See full document
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Enhancing the performance of migration process using aco algorithm and rsa encryption over cloud environment
... Further effort in augmenting and refining both scenarios and patterns is required in the future. Providing tooling support for applying the application data migration methodology discussed in Section , Data migration ... See full document
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