neural network method
Modelling and predicting of MODIS leaf area index time series based on a hybrid SARIMA and BP neural network method
... linear method or nonlinear method. In this paper, SARIMA, BP neural network and a hybrid method of SARIMA-BP neural network were used for modeling and predicting MODIS LAI ...
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Deep neural network method for the prediction of xylitol production
... deep neural network has been used. Deep neural network is one of the methods from deep ...learning method to predict binding affinity of a protein to a DNA or RNA sequence in two ...
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Performance comparison of three artificial neural network methods for classification of electroencephalograph signals of five mental tasks
... of neural network with resilient back propagation training method, support vector machine and radial bases function Neural Net- work for classifying of mental tasks ...Function) neural ...
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Prediction of Gum Disease Severity on the basis of Symptoms and Risk factors using Neural Network
... artificial neural network mode is helpful in clinical ...saving method. In proposed method we took symptoms and risk factors of gum diseases as input to the neural network model ...
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Oil Price Forecasting Based on EMD and BP AdaBoost Neural Network
... The neural network method based on wavelet transform has been extensively used in financial time-series analysis, but wavelet analysis still has some defects, which cannot be adaptively decomposed, ...
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Text Dependent Speaker Recognition using MFCC features and BPANN
... the network is of size 200 × 65 for a cluster size of ...direct method. The comparison of neural network based and minimum distance based classifiers are shown in Table 6 from which it can be ...
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A SHORT-TERM TRAFFIC FLOW FORECASTING METHOD BASED ON STATE IDENTIFICATION.
... prediction method based on knowledge discovery, Include the methods of neural network, Nonparametric regression, Support vector machine ...(SVM). Neural network method is to use ...
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A method of gene diagnosis based on Hopfield neural network
... Hopfield neural network, one is when the transfer function of neurons in network is monotonically increasing and the weight matrix of the network is symmetric, the energy of the network ...
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ARTIFICIAL NEURAL NETWORK BASED TOLERANCE ANALYSIS METHOD
... The neural fitting tool (nftool) in Matlab shown in figure 11 is chosen for creating and training the neural network. In nftool window the collected data of component dimensional tolerances as input ...
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Attr2vec: A Neural Network Based Item Embedding Method
... in neural embedding methods in natural language processing (NLP) tasks have greatly increased the ability of computers to solve problems [4, 5, 6, ...the neural network based language model NNLM [5] ...
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New Steganalysis Method using GLCM and Neural Network
... media, method of Steganography, ...this method introduces into an image and also it is extremely simple to implement ...layers neural network to detect the presence of embedded messages in the ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks in literature re- search by Aston ...“the network can be taught to recognize individual writing styles, and the researchers used it to compare works attributed to Shakespeare and his ...
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Face Recognition Techniques: A Survey
... This method is to recognize a multiview face (i.e., to recognize a face under different views) through optimization of multiple single-view face recognitions [26]. Many face descriptors show quite satisfactory ...
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Evaluation of Stiffened End Plate Moment Connection through Optimized Artificial Neural Network
... optimized parameters of coupled ANNs and GA have been presented. In addition in this table, maximum and optimized numbers of nodes in the hidden layer, prob- ability of mutation and crossover have been presented as well. ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... layer neural network back propagation ...layer neural networks outperform the previous work in terms of ...layer neural network back propagation al- ...
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Comparing Feature Selection Method For Neural Network Classification
... In the classification of neural network system, feature selection plays a major role for the purpose of classification problem. A set of attribute that relevant, irrelevant or redundant can be huge. ...
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Short Term Load Forecasting With Feed Forward Neural Network Algorithm
... Load forecasting plays an important role in power system planning and operation. Basic operating functions such as unit commitment, economic dispatch, fuel scheduling and unit maintenance, can be performed efficiently ...
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Adaptive Neuro Fuzzy Inference System based Optical Character Recognition
... Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. ...
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OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... BP neural network is selected as the weak ...BP network is forward feed network with three layers: input layer, hidden layer and output ...
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Cholesky ANN models for predicting multivariate realized volatility
... the network may lead to overfitted out-of-sample forecasts and the number of connection weights may significantly ...the network, the parameters have been trained with 300 different starting ...the ...
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