backpropagation algorithm
Performance Of Resilient Backpropagation Algorithm In Face Recognition
... Resilient Backpropagation algorithm in face recognition where Resilient Backpropagation is a learning heuristics for supervised learning in artificial neural ...
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Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World
... [5]. Backpropagation is one method that is quite good at making predictions ...the backpropagation algorithm allows to avoid difficulties by using learning rules that are similar to the plasticity of ...
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Radial basis function neural network learning with modified backpropagation algorithm
... As a result of the above mentioned benefits, RBFNN enjoys patronage in science and engineering. According to Yu et al. (1997) RBFNN has only three layers. Radial function is applied as activation function for all the ...
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Three-term backpropagation algorithm for classification problem
... BP algorithm is one of the most popular methods in training ...of backpropagation (Fogel et al., 2003). The first defines backpropagation as a procedure for efficiently calculating the derivatives of ...
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Parallelization of Backpropagation Algorithm and Benchmarking
... The gradient is fed to the optimization method which updates the weights to minimize the loss function. Back propagation output for each input value in order to gradient (https://mattmazur.com/ step ...
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Implementation of Backpropagation Algorithm: A Neural Net- work Approach for Pattern Recognition
... According to author Jayanta Kumar Basu ,Debanath Bhattacharyya from Computer Science and Engineering Department of Heritage Institute of Technology, Kolkata , India on “Use of Artificial Neural Network in Pattern Recog- ...
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Closed loop control using a backpropagation algorithm: a practicable approach for energy loss minimisation in electrical drives
... Abstract: In general, optimal controls are computed off line and subsequently applied in real time but this approach is impracticable due to lack of robustness with respect to the plant modelling errors and unknown ...
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An Energy Backpropagation Algorithm
... convergence algorithm, if unknown input image is learned, then converge the stored image with the minimum energy function ...learning algorithm, we divide the image into ...the backpropagation ...
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Development of a Genetic based Neural Network System for Online Character Recognition
... genetic algorithm as a tool to find an optimal subset of the stroke ...standard backpropagation and genetic algorithm for recognition of uppercase ...the algorithm of feed forward BPNN ...
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Machine learning in Dynamic Adaptive Streaming over HTTP (DASH)
... the backpropagation algorithm (BA), the Neural Network BAs also covers Bayesian regularization and early stopping, which ensure the generalization ability of trained networks ...
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Analyzing The Personal Behavior Of Adolescence Using Artificial Neural Networks
... Multilayered Backpropagation Algorithm to predict student’s absenteeism in ...with Backpropagation Algorithm and the reason for students taking leave to college was identified from the ...
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A Framework on Hand Gesture Recognition Using Fuzzy-Logic with Backpropagation Neural Network Algorithm
... In this paper we propose a lightweight hand gesture recognition system, based on feature extraction and recognition approach, implementing the Evolving Fuzzy Clustering Method and backpropagation algorithm. ...
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Model of Electric Power Load by Adaptive Neural Network
... The Backpropagation algorithm has become a common algorithm used for training feed-forward multilayer ...Square algorithm that minimizes the mean square error between the target output and the ...
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Artificial Neural Networks A Review of Applications of Neural Networks in the Modeling of HIV Epidemic
... like backpropagation, Levenberg-Marquardt, and Bayesian rule algorithms were employed to train the MLP ...using backpropagation algorithm produced the best performance with ...
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Design and Implementation of Prosthetic Hand Control Using Myoelectric Signal
... ANN Backpropagation algorithm learning outcomes were tested with 15 sets of test ...ANN Backpropagation algorithm was compared for the ability in classifying provided test data ...ANN ...
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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 required ...
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A FUZZY BASED BUFFER SPLIT ALGORITHM FOR BUFFER ATTACK DETECTION IN INTERNET OF THINGS
... The first phase of implementing the feed-forward propagation sequence was intended to find an effective way to input the pattern into the network, after extracting feature vectors having (200) elements for each symbol ...
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Stock Market Prediction Model by Combining Numeric and News Textual Mining
... II. Backpropagation Algorithm in Neural Network [6] The study used three-layer (one hidden layer) multilayer feed- forward neural network model trained with backpropagation ...
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Prediction Of Heart Disease Using Back Propagation MLP Algorithm
... with BackPropagation algorithm using 15 input attributes gives the highest accuracy BackPropagation algorithm with momentum and variable learning rate was used to train the ...
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Date Fruits Classification using MLP and RBF Neural Networks
... by Backpropagation algorithm has two ...The backpropagation training algorithm is an iterative gradient designed to minimize the mean square error between the actual output of multilayer ...
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