[PDF] Top 20 An Optimized Back Propagation Learning Algorithm with Adaptive Learning Rate
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An Optimized Back Propagation Learning Algorithm with Adaptive Learning Rate
... — Back Propagation (BP) is commonly used algorithm that optimize the performance of network for training multilayer feed-forward artificial neural ...in learning and it sometimes gets trapped ... See full document
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Hybrid Optimized Back propagation Learning Algorithm for Multi layer Perceptron
... ABSTRACT Standard neural network based on general back propagation learning using delta method or gradient descent method has some great faults like poor optimization of error-weight obj[r] ... See full document
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NEW MODEL TRANSFORMATION USING REQUIREMENT TRACEBILITY FROM REQUIREMENT TO UML BEHAVIORAL DESIGN
... swarm algorithm to optimize BP network's initial weights and initial thresholds, uses adaptive learning rate and additional momentum BP algorithm to adjusted the network weights and ... See full document
7
Optimal Parameter Selection Using Three-term Back Propagation Algorithm for Data Classification
... with adaptive momentum and adaptive learning rate value during the learning ...proposed algorithm, known as, (BPGD-A3T), presents better convergence rate and can avoid the ... See full document
7
Artificial Intelligent Modeling and Optimizing of an Industrial Hydrocracker Plant
... the adaptive parameters is of vital importance for the performance of the adaptive ...hybrid learning algorithm for ANFIS which is faster than the classical back-propagation ... See full document
13
Second Order Learning Algorithm for Back Propagation Neural Networks
... the learning process in feed forward neural networks (MLFNN) have been recently studied and several new adaptive learning algorithms have been ...popular learning algorithm is the batch ... See full document
10
Estimating of Scour in Downstream of the Water Level Regulation Structures
... with learning algorithm of error back propagation (BP) were used to estimate maximum water scour depth, and the model which has seven neurons in its hidden layer was produced as the most ... See full document
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Effective Learning Rate Adjustment of EASI Algorithm Based on the Fuzzy Neural Network
... for adaptive learning for the mixing ...gradient algorithm(NGA)[4], EASI and so ...bigger learning rate, the faster convergence rate and the worse stability ... See full document
12
The effect of adaptive parameters on the performance of back propagation
... The learning rate is one of the most effective means to accelerate the convergence of BP learning which values lies between 0 , 1 ...of learning rate value. The learning ... See full document
50
A Survey On Backpropagation Algorithms For Feedforward Neural Networks
... -The Back-propagation (BP) training algorithm is a renowned representative of all iterative gradient descent algorithms used for supervised learning in neural ...BP learning ... See full document
5
ANN in Medical Field Survey Paper
... Network optimized with Genetic Algorithm in prediction of heart disease diagnosis with UCI ...was optimized with Genetic Algorithm and proved ...were optimized with genetic ... See full document
7
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 ... See full document
7
BPGD-AG: A New Improvement Of Back-Propagation Neural Network Learning Algorithms With Adaptive Gain
... in back-propagation ...that learning rate, momentum constant and gain of the activation function have a significant impact on training ...of learning rate and/or gain cause ... See full document
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Online Full Text
... the adaptive network layers to reduce the amount of computation in the ...the back-propagation (BP) algorithm having an optimal learning rate (adaptive learning ... See full document
6
A new back propagation neural network optimized with cuckoo search algorithm
... (BPNN) algorithm [11]. However, the BPNN algorithm suffers from two major draw- backs: low convergence rate and ...the back propagation algorithm including the conjugate gradient ... See full document
14
Forecasting Fuzzy Delphi and Hybrid intelligent system for ERP Architecture through the Scientific Private Cloud
... To enhance the competitive advantage in a constantly changing environment, the manager of a company must make the right decision at the right time based on the information at hand. The Enterprise Resource Planning System ... See full document
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Neural network method for control valve cost estimation on the EPC project bidding
... Learning rate determines how efficiently and quickly the convergence of back propagation ...algorithm. Learning rate is a control parameter that regulates step magnitude ... See full document
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Image Reconstruction Using Multi Layer Perceptron (MLP) And Support Vector Machine (SVM) Classifier And Study Of Classification Accuracy
... and back-propagation neural network (BPNN) has been applied successfully in many areas, for example, rule extraction, classification and ...the back-propagation algorithm for training ... See full document
6
How Ties to Professional Support Networks Impact Social Outcomes among Homeless Youth
... Deep learning application on neural networks allows for the discovery of intricate patterns and structures in large sets of data through the use of back propagation algorithm [24], which[r] ... See full document
77
Survey on Effective Kidney Stone Disease Diagnosis Using ANN
... gradient back propagation and Levenberg-Marquardt back propagation algorithm for training the neural ...Levenberg-Marquardt propagation and outcomes are measured, then the same ... See full document
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