backpropagation through time learning algorithm
Comparative Study of Particle Swarm Optimization (PSO) and Firefly Algorithm (FA) on Least Median Squares (LMedS) for Robust Backpropagation Neural Network Learning Algorithm
... towards time series-prediction arena, but the presence of outliers that usually occur in the time series data may pollute the network training ...common algorithm to train the network is the ...
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Backpropagation neural network as earthquake early warning tool using a new modified elementary Levenberg–Marquardt Algorithm to minimise backpropagation errors
... alarms through a decision-making process that belonged to post- mortem ...warning time was retrieved ...warning time may be sub- jectively determined as soon as ...
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An Energy Backpropagation Algorithm
... Both the EBP and the SBP algorithms were implemented and tested on images of different sizes. The samples of the images were taken from a database of fingerprint images and images of Baghdad city. The images are of BMP ...
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RNN language model with word clustering and class-based output layer
... truncated backpropagation through time algorithm (BPTT) is used for training the RNNLMs using ten time ...the learning rate is ...
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Moisture Prediction in Maize Using Three Term Back Propagation Neural Network
... less time and higher accuracy assumes greater ...Term Backpropagation network is proposed as a prediction tool for moisture content on ...reduces learning stalls in the conventional neural ...genetic ...
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Parallelization of Backpropagation Algorithm and Benchmarking
... propagation Algorithm is a technique to train Artificial Neural Networks to calculate the error function with respect to all the ...propagation Algorithm is a supervised learning approach in neural ...
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Radial basis function neural network learning with modified backpropagation algorithm
... In addition, to train RBFNN, we can take a two-step training strategies. The first step is called unsupervised learning. Unsupervised learning is used to determine RBFNN centres and widths of the clusters ...
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Comparison between Trinity Unsupervised Data Extraction and Data Extraction Using Artificial Neural Network
... using backpropagation algorithm is a supervised learning and deals with KDD cup dataset as input and further process of research is done on this basis so that mining could take place building the ...
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Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World
... and time series data from these problems, which are generally complicated by estimating accuracy that is not easily achieved, so that it requires more advanced techniques ...[5]. Backpropagation is one ...
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Development of a Genetic based Neural Network System for Online Character Recognition
... training time and recognition ...(genetic algorithm) into modified backpropagation neural network to enhance the performance of character ...Genetic algorithm was use as feature selection to ...
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Three-term backpropagation algorithm for classification problem
... Genetic Algorithm (GA) to determine learning rate and momentum ...the learning rate and momentum, but is changes the structure of the BP ...improved algorithm with stochastic attenuation ...
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Neural Networks For Financial Time Series
... Supervised learning: when we have a set of training data including typical input examples with the corresponding ...appropriate algorithm (usually backpropagation that is a supervised learning ...
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Neural Network For Face Recognition Using Different Classifiers
... Since the network weights are initialised to random values, it is unlikely that reasonable outputs will result before training. The weights are adjusted to reduce the error by propagating the output error backward ...
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Date Fruits Classification using MLP and RBF Neural Networks
... with backpropagation and radial basis function RBF ...with backpropagation and RBF, which is consistent with the best results reported in the literature for the same data base and testing ...
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Backpropagation Neural Network Algorithm for Water Level Prediction
... going through the media ...real time using TCP / IP communication ...real time becomes an obstacle in measuring water levels in flood ...Real time data obtained with WSN will be utilized in ...
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Backpropagation Neural Network Based on Local Search Strategy and Enhanced Multi-objective Evolutionary Algorithm for Breast Cancer Diagnosis
... the backpropagation neural ...genetic algorithm (NSGA-II). Then, we hybrid the enhanced algorithm with the local search strategy to ensures the acceleration of the convergence speed to the non- ...
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How to Make a Mudsparkler
... Note that in principle the opposite of overfitting can occur as well. This is called underfitting, and occurs when a learning algorithm performs poorly on both the train- ing data and on unseen data. Due to ...
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Distributed Collaborative Approach to Botnet Detection
... We started by writing script in Python Language to periodically fetch questionable payload data that was dumped into MySQL database by Snort. A hash for the payload is then computed and the script appends a question to ...
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Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)
... novel learning model to determine (a) the optimal time to re-route the traffic flows, and (b) to change the bitrate of the ...a learning-based ...the learning model aims to minimize (1) the ...
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Cascade-Forward Algorithm to Extract Hidden Rules of Gastric Cancer Information Based on Ontology
... Feed-forward backpropagation network is simply the application of backpropagation procedure into the feed-forward networks such that every time the output vector is presented, it is compared with the ...
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