backpropagation neural network learning
A subjective job scheduler based on a backpropagation neural network
... the neural network is an elementary information-processing ...artificial neural network, first it is to be decided how many neurons are to be used and how the neurons are to be connected to ...
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Daily Network Traffic Prediction Based on Backpropagation Neural Network
... a network traffic that connects the ICT Center and all the faculties, institutes, and units with a bandwidth capacity of 150 ...in learning and teaching, such as e-Learning, e-Library, Academic ...
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An ensemble learning algorithm for blind signal separation problem
... Bayesian learning algorithms is based on the assumptions that the quantities of interest are governed by probability distributions, and that optimal decisions can be made by reasoning about these probabilities ...
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Rainfall Forecasting Using Backpropagation Neural Network
... of Neural Networks are Multilayer Perception (MLP) that being combined with Backpropagation ...propagation Neural Network resulted 94,36% accuracy, while research by Vamsidhar et ...that ...
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Backpropagation neural network as earthquake early warning tool using a new modified elementary Levenberg–Marquardt Algorithm to minimise backpropagation errors
... Figure 3c presented the predicted results of the LMA and M-LMA from the proximal Station-TCU084 using the best learning rate for both methods, determined to be 0.2. The predicted results of the M-LMA had smaller ...
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Development of a Genetic based Neural Network System for Online Character Recognition
... standard backpropagation and genetic algorithm for recognition of uppercase ...optical backpropagation neural ...a backpropagation network algorithm combined with genetic algorithm to ...
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Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World
... the Backpropagation Neural Network ...that neural networks with cross validation 80% Training and 20% validation and testing as well as learning rate ...
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INTERNETWORKING INDONESIA JOURNAL
... unsupervised learning, there is no trainer present to hand over the desired output and the network, therefore the network tries to learn by itself, organizing the input instances of the ...include ...
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Backpropagation Neural Network Based on Local Search Strategy and Enhanced Multi-objective Evolutionary Algorithm for Breast Cancer Diagnosis
... for learning and train the neural ...the network. Therefore, the decision to choose the best network architecture depends on the automatic design of the ...
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Speaker Independent Vowel Recognition using Backpropagation Neural Network on Master Slave Architecture
... The eleven steady state vowels of British English in the dataset are i , O, I, C:,E,U:,A,u.a:, 3: Y. The speech signals were low pass filtered at 4.7 kHz and then digitized to 12 bits with a 10 kHz sampling rate. Twelfth ...
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Model of Electric Power Load by Adaptive Neural Network
... a learning law for updating the weights of interconnection between two ...of Backpropagation training algorithm of such ...and learning factors which are often chosen by trial and ...for ...
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Backpropagation Neural Network Experiment on Human Face Recognition
... For localization and normalization, the local view method for eigenface (use of a machine learning) approaches to deal with scaling variation. The image processing and computer vision have investigated the number ...
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Date Fruits Classification using MLP and RBF Neural Networks
... by Backpropagation algorithm has two ...the network input layer. The network propagates the input pattern from layer to layer until output pattern is generated by the output ...the network ...
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Radial basis function neural network learning with modified backpropagation algorithm
... Artificial Neural Network (ANN) was developed as a parallel distributed system that is inspired by the biological learning process of the human ...of learning to solve problems through ...
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Texture Feature On Determining Quantity of Soil Organic Matter For Patchouli Plant Using Backpropagation Neural Network
... Abstract. Patchouli (Pogostemon Cablin Bent) has higher PA (Patchouli Alcohol) and oil production if grown in soil containing 75% organic matter. One way that can be used to detect the content of organic matter is to use ...
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Prediction of Seismic zone in India using Neural Network Algorithms
... seismology. Neural network performs a key task in the prediction of ...The neural network architecture are created with different input layer and hidden layers with deep learning ...
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Modular Neural Network Approach for Data Classification
... modular neural network in predicting classes of different ...feedforward backpropagation neural network with supervised learning is proposed to ...proposed neural ...
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APPLICATION OF CELLULAR AUTOMATA FOR MODELING AND REVIEW OF METHODS OF MOVEMENT OF A GROUP OF PEOPLE
... Patel et al. [6] proposed hybrid forecasting models to predict (t + n)th day closing price of both S&P BSE Sensex and CNX Nifty indexes. They used technical indicators as inputs and Support vector regression to ...
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Prediction of Salinity Variations in a Tidal Estuary Using Artificial Neural Network and Three Dimensional Hydrodynamic Models
... A neural network consists of a large number of simple processing elements that are called neurons and ...the network, i.e ., the model neuron, is shown in Figure 2. Neural networks can be ...
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Study on Experiments of Artificial Neural Network Using Spatial Data
... The third parameter, the momentum; it correlation values 0.005 have no more than 50% overall accuracy. This means that the momentum value that is too small is less used as a reference for network simulation, in ...
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