adaptive back-propagation learning
An Optimized Back Propagation Learning Algorithm with Adaptive Learning Rate
... of back propagation learning is the learning rate which values lies between ...Controlling learning rate value has become a crucial factor for neural network learning algorithm ...
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Second Order Learning Algorithm for Back Propagation Neural Networks
... the learning rate value to achieve a target error equal to ...with adaptive changes in weight, bias and gain ...an adaptive gain with an initial value of unity for the gain parameter for all output ...
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BPGD-AG: A New Improvement Of Back-Propagation Neural Network Learning Algorithms With Adaptive Gain
... general back-propagation ...the learning rate, using momentum, gain tuning of activation ...efficient learning in feed forward neural networks using momentum ...the ...
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Optimal Parameter Selection Using Three-term Back Propagation Algorithm for Data Classification
... The back propagation (BP) algorithm is the most popular supervised learning method for multi-layered feed forward Neural ...BP learning algorithm have been made by researchers, but the local ...
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Forecasting Fuzzy Delphi and Hybrid intelligent system for ERP Architecture through the Scientific Private Cloud
... of learning by FCBPN: We use hybrid sales forecasting system based on fuzzy Delphi, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate ...
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The Effect of Adaptive Gain and Adaptive Momentum in Improving Training Time of Gradient Descent Back Propagation Algorithm on Classification Problems
... The back propagation algorithm has been successfully applied to wide range of practical ...slow learning convergence velocity and easy convergence to local ...the back propagation ...
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The effect of adaptive gain and adaptive momentum in improving training time of Gradient Descent back propagation algorithm on classification problems
... conventional back propagation ...the learning rate, using momentum and gain tuning of activation ...the learning fashion of training examples is batch ...the learning procedure, which ...
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Online Full Text
... the back-propagation algorithm is widely used and a powerful training technique [5, 8, ...the back-propagation (BP) algorithm having an optimal learning rate (adaptive ...
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Study and Review of Various Image Classification Methods for Diabetes Mellitus Detection
... using Back propagation algorithm. Then Neighbourhood based Modified Back propagation using Adaptive Learning Parameters (ANMBP) method is employed to model the relationship ...
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The effect of adaptive parameters on the performance of back propagation
... first learning rules for the McCulloch and Pitts Neural Network known as Hebbian Learning Rule by dealing with ways in which synapses can change their efficiencies (Hebb, ...an adaptive linear ...
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An Efficient Neural Network Based System for Diagnosis of Breast Cancer
... unsupervised learning methods are those in which, the neural networks are trained only with input ...of learning is accomplished through a process that proceeds ...unsupervised learning process, as ...
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Unleashing Power of Artificial Intelligence for Network Intrusion Detection Problem
... Since the operations of normal packets are specified and they show expected behaviour, we could use the knowledge based (misuse) IDS detection, while unexpected activity (presumably an intrusion would be unusual) is ...
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Artificial Neural Network Prediction of Aluminium Metal Matrix Composite with Silicon Carbide Particles Developed Using Stir Casting Method
... on learning a set of parameters (weights), aimed at replacing the traditional explicit constitutive equations used to describe material behavior (Bezerra et ...
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Review Techniques of Data Privacy in Cloud Using Back Propagation Neural Network
... performance. Learning efficiency measured in term of learning time ...of learning time. For two party scenario compare our learning scheme with Chen’s Scheme in term of learning time ...
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Optimization of Traveling Salesman Problem based on Adaptive Affinity Propagation and Ant Colony Algorithms
... The Travelling Salesman Problem can simply be stated as: if a traveling salesman wishes to visit exactly once each of a list of cities and then return to the home city, what is the least costly route the traveling ...
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Effect of fuzzy partitioning in Crohn's disease classification: a neuro-fuzzy-based approach
... Abstract: Crohn’s disease (CD) diagnosis is a tremendously serious health problem due to its ultimately effect on the gastrointestinal tract (GI) that leads to the need of complex medical assistance. In this study, the ...
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Horse Racing Prediction Using Artificial Neural Networks
... In general, there are three fundamentally different classes of network architectures in ANNs- Single-Layer Feedforward Networks (SLFF) which have an input layer of source nodes that projects onto an output layer of ...
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Hybrid Supervised Learning in MLP using Real coded GA and Back propagation
... compared back-propagation with a genetic algorithm for neural networks ...based learning is used to find near-optimal solutions globally from search space without computing gradient ...based ...
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Review: Face Detection and Recognition Techniques
... Abstract- Human face plays an important role in our social interaction, conveying people’s identity but it is a dynamic object and has a high degree of variability in its appearences.So to overcome this variability Face ...
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Estimating of Scour in Downstream of the Water Level Regulation Structures
... As it was mentioned, in addition to optimized equations, artificial neural networkis used to calculate maximum scour depth. So in this research MLP networks by error back propagation (BP) training algorithm ...
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