backpropagation based training method
Daily Network Traffic Prediction Based on Backpropagation Neural Network
... prediction method based on BPNN. The performance of the training algorithm can be used to estimate the architectures of the ...neuron. Based on the results of this research concluded that ...
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INTERNETWORKING INDONESIA JOURNAL
... one method that has been known for prediction problems. The method can also be used to forecast based on the pattern of events in the ...One method that can be used to improve the weight of ...
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Research status and applications of nature-inspired algorithms for agri-food production
... about backpropagation (BP) training algorithm for multilayer feedforward ANN was published [34,35] ...learning based on statistical ...learning method has a lot of advantages over the man-made ...
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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 ...the method of gradient ...[11] based on a graphical approach in which the algorithm ...
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Analysis on the Comparison Exponential Smoothing and Neural Network in Forecasting the Trend of Toddler Nutritions in Community Health Centre
... Time-Series Based Neural Network Backpropagation ...network backpropagation method to predict the monthly inflation level in ...data training while the other 20% were used as data ...
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Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning
... The transparency of the decision making process has always been an issue in diagnos- tic decision making. Undoubtedly, it would be advantageous to be able to trace the logi- cal flow at every step of the way, as was done ...
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Backpropagation neural network as earthquake early warning tool using a new modified elementary Levenberg–Marquardt Algorithm to minimise backpropagation errors
... by training the network using 342 earthquakes recorded by 23 different stations (about 5000 ...this method, and a failure could affect the ability of an EEW if the traces have high ...a method for ...
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A FUZZY BASED BUFFER SPLIT ALGORITHM FOR BUFFER ATTACK DETECTION IN INTERNET OF THINGS
... a method is able to recognize cuneiform symbols through the use of neural ...Finally, Backpropagation Algorithm was used in recognition with (20) hidden nodes and at the learning rate ...
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Using constraints to improve generalisation and training of feedforward neural networks : constraint based decomposition and complex backpropagation
... this method of reporting the speed performances of an algorithm by quoting only the time necessary to train a given problem (and the machine) is used very ...
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AUTOMATIC IDENTIFICATION OF RING ENHANCING LESION PATTERN IN CASES OF BRAIN INFECTION AND METASTASIS BRAIN TUMOR BASED ON INVARIANT MOMENT FEATURES CLASSIFICATION
... invariants method is shown in Figure ...BPNN training process gives the threshold values 1 for brain infection, ...using backpropagation neural network with sigmoid activated function that the target ...
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An ensemble learning algorithm for blind signal separation problem
... 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 together with the ...approach ...
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Cascade-Forward Algorithm to Extract Hidden Rules of Gastric Cancer Information Based on Ontology
... Kirshners et al. used a data set including 819 samples (24 positive and 795 negative samples) and 31 features and three algorithms CN2 Rules and C4.5 and Naive Bayes to diagnose stomach cancer. The results showed that ...
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Design and Implementation of Prosthetic Hand Control Using Myoelectric Signal
... freely based on their own, making the same movement in ...into training data for ANN Backpropagation and recalculated for the value of accuracy, as shown in ...
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Prediction Of Heart Disease Using Back Propagation MLP Algorithm
... SAS based software ...integral based FDHMM (Fuzzy Discrete Hidden Markov ...integral based method was better than the performances of Artificial Nerual Network (ANN) and HMM based ...
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Backpropagation Neural Network Based on Local Search Strategy and Enhanced Multi-objective Evolutionary Algorithm for Breast Cancer Diagnosis
... The NSGA-II is one of the modern MOEAs that integrates a non-dominating sorting approach [30], which provides accelerated speed compared to any other multi- objective evolutionary algorithm, and identifies the crowded ...
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An Energy Backpropagation Algorithm
... The feed forward backpropagation (FFBP) network is a very popular model in neural networks. It does not have feedback connections, but errors are backpropagated during training. Least mean squared error ...
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Neural Network For Face Recognition Using Different Classifiers
... Abstract: In this paper I proposed a novel technique for Face Detection and Recognition by Neural Network for Face Recognition using different Classifier. It is advance computer vision of human Face recognition being ...
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A Hybrid of Artificial Bee Colony, Genetic Algorithm, and Neural Network for Diabetic Mellitus Diagnosing
... their training algorithms have become increasingly important for modeling and optimization in many fields of science and ...other training types due to its great capability in-universe approximation and ...
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Adaptive Analytical Approach to Lean and Green Operations
... production. Based on Figure 3, the industrialists from the manufacturing have indicated that employee attitude and performance will contribute to L&G ...
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Comparative Study of Optical Character Recognition Techniques
... 3. Genetic Algorithm Optimized Neural Network: Genetic algorithm runs twice in this system, first is to determine the network architecture and sec, to determine the weight for the network synapses. Basic processes in ...
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