Back-propagation neural networks
A FACE RECOGNITION SYSTEM BASED ON PRINCIPAL COMPONENT ANALYSIS USING BACK PROPAGATION NEURAL NETWORKS
... Face recognition has received substantial attention from researches in biometrics, pattern recognition field and computer vision communities. Face recognition can be applied in Security measure at Air ports, Passport ...
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Applying Back Propagation Neural Networks in the Prediction of Management Associate Work Retention for Small and Medium Enterprises
... Abstract Since investment in employee education and development represents a significant capital expenditure, the recruitment of employees whose personal characteristics, professional skills and abilities meet the ...
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A Comprehensive Study of Hybrid Genetic Algorithm based Back-propagation Neural Networks
... “Neural Networks- a Systematic Introduction” a gradient search method for adapting the weights was developed, which were based on minimizing the root-mean squared error, known as LMS or Least Mean ...into ...
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Second Order Learning Algorithm for Back Propagation Neural Networks
... In this paper, a new and improved training method is introduced for fast supervised learning method in the neural network. The performance of the proposed first order and second order methods with adaptive gain ...
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Image Reconstruction Using Super Resolution and Back-propagation Neural Networks
... Chao Dong et.al [3], proposed a deep learning method for single image super resolution (SR), method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep ...
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Genuine and Forged Offline Signature Verification Using Back Propagation Neural Networks
... a Neural Network, we can simply demonstrate it saying: "this will be the exact output, for this ...of Neural Network about the inputs required is that, even if some of the inputs that are applied are ...
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The Effect of Pre-Processing Techniques and Optimal Parameters selection on Back Propagation Neural Networks
... the Back Propagation (BP) neural network sticking to local optimal, convergence speed, and the increase in computational cost associated with its learning process, this study explored the influence ...
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Feature Extraction Techniques of Non Stationary Signals for Fault Diagnosis in Machinery Systems
... of back-propagation neural networks to establish them as the most widely-used algo- ...neural networks. The vibration acceleration spectrum is used as the neural network ...
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PREDICTION OF MONTHLY RAINFALL OF MANSA REGION USING ARTIFICIAL NEURAL NETWORK (ANN)
... Forward Back propagation, Cascade Forward Back propagation neural networks model for predicting the average monthly rainfall of Mansa ...forward back propagation ...
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Forecasting Fuzzy Delphi and Hybrid intelligent system for ERP Architecture through the Scientific Private Cloud
... This search describes a hybrid system based on the Fuzzy Delphi method, fuzzy clustering and Back-propagation Neural Networks with an adaptive learning rate (FCBPN) for sales forecasting.The ...
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ATM Security using Machine Learning
... --------------------------------------------------------------------------***---------------------------------------------------------------------------- Abstract - Due to use of outdated technology and lack of basic ...
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Estimating of Scour in Downstream of the Water Level Regulation Structures
... Artificial neural networks (ANNs) 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 ...
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DEVELOPMENT OF GENETIC ALGORITHM BASED HYBRID NEURAL NETWORK MODEL FOR PREDICTING THE ULTIMATE FLEXURAL STRENGTH OF FERROCEMENT ELEMENTS
... Artificial Neural Networks are highly non-linear and can capture complex interactions among input/output variables in a system without any prior knowledge about the nature of these ...of neural ...
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A Robust Intrusion Detection System by Utilizing Support Vector Machine and Error Back Propagation Neural Network
... In this work solving the computer networking problem to give the specific way to prevent the security problems intrusion detection system (IPS) has a main techniques to secure the computer networks problems. Many ...
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INVESTIGATING DATA MINING BY ARTIFICIAL NEURAL NETWORK: A CASE OF REAL ESTATE PROPERTY EVALUATION
... artificial neural networks. Back propagation algorithm has been used to train the neural network with a set of data samples of real estate ...
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Content Based Message Filtering System for OSN User Walls
... on back propagation networks A back propagation network is a synthetic neural network that uses back propagation functions as activation ...of back ...
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Review on Financial Forecasting Using Neural Network and Data Mining Technique
... Hopfield network is the most typical feedback network model, it is one of the models which are most commonly studied now. The Hopfield network is the monolayer constituted by the same neuron, and is also a symmetrically ...
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A new Cuckoo Search Based Levenberg Marquardt (CSLM) algorithm
... Abstract. Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural ...traditional back propagation optimized with Levenberg ...
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Application of Artificial Neural Network and Genetic Algorithm for Predicting three Important Parameters in Bakery Industries
... two neural networks were designed: the first for modeling water absorption of flour and development time of dough and the second for modeling farinograph quality ...both networks were seven ...
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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] ...
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