feed-forward network
A Data Mining Model by Using ANN for Predicting Real Estate Market: Comparative Study
... Feed forward networks often have one or more hidden layers of sigmoid neurons followed by an output layer of linear ...the network to learn nonlinear and linear relationships between input and output ...
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Stock Market Prediction using Feed forward Artificial Neural Network
... Third, artificial neural networks have been claimed to be excellent general function approximates. It is proved that a Multi-layer perceptrons (MLP) can approximate any complex continuous function that enables us to ...
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Hybrid neural networks in rainfall-inundation forecasting based on a synthetic potential inundation database
... neural network (RiHNN) that combines principal component analysis with a feed-forward network to forecast the real-time 1-hour-ahead water depth of inundation at distributed representative ...
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Performance Analysis of Face Recognition by Principal Component Analysis and Feed Forward Neural Network
... of network performance and architecture will almost always result in a slow training process due to the added algorithmic complexity ...E. Feed Forward ...
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A Novel Soft Computing Authentication Scheme for Textual and Graphical Passwords
... to Feed Forward Network and weights for network are retrieved from database with index as username and used for network so that the output of network will be the user password ...
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Glaucoma Recognition and Segmentation Using Feed Forward Neural Network and Optical physics
... using feed forward ...The feed forward neural network is used to detect weather the glaucoma disease is in initial or final stage, or disease can be cured or ...
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Prediction of Weld Bead Geometry and Penetration in Electric Arc Welding using Artificial Neural Networks
... propagation network is a multilayer feed forward network with a different transfer function in the artificial neuron and more powerful learning ...the network must be presented many ...
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A Feed-Forward Neural Network Model For The Accurate Prediction Of Diabetes Mellitus
... multi-layered feed-forward network with 8 input nodes, 10 hidden nodes, and 1 output node was ...the network as ...neural network were initialized using the MATLAB ...the network ...
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Machine Learning-Based Node Selection for Cooperative Non-Orthogonal Multi-Access System Under Physical Layer Security
... Abstract: Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage, and interference ...
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Crop Cost Forecasting using Artificial Neural Network with feed forward back propagation method for Mysore Region
... of feed forward ANNs. First term, “feed forward” defines how this neural network works and recalls patterns and the term “back propagation” defines how this kind of neural networks are ...
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Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
... neutral network models, which have been used in this study, and second, to find which of these models can make a more accurate forecast the return of Tehran Stock Exchange ...neutral network models in ...
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Telecom Voice Traffic Prediction for GSM using Feed Forward Neural Network
... to feed forward multilayer ...the network until it reaches to desired performance ...neural network are moved along the negative of the gradient of the performance function (surface of mean ...
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Prediction of Tourist Quantity Based on RBF Neural Network
... neural network [1], in which the principle and algorithm of RBF neural network is ...neural network model shows based on RBF neural network tourist quantity prediction model can exactly ...
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Short Term Load Forecasting With Feed Forward Neural Network Algorithm
... Load forecasting plays an important role in power system planning and operation. Basic operating functions such as unit commitment, economic dispatch, fuel scheduling and unit maintenance, can be performed efficiently ...
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Palmprint Biometrics using Feed Forward Back Propagation Neural Network
... In structural feature based methods [4] [5] [6] structural information, such as principle lines, wrinkles, minutiae points etc., can be used as features of palm. Although line features can be detected even in the ...
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Feed forward neural network application for classroom reverberation time estimation
... In this experiment, 60%, 20%, and 20% data from the dataset is used as the training data, validation data and testing data, respectively. The training data is used to train and fit the models; the validation data is used ...
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Brain Tumor Detection and Classification with Feed Forward Back Propagation Network
... the parts of the body. Recognition of automated brain tumor in Magnetic resonance imaging (MRI) is a difficult task due to complexity of size and location variability. Previous methods for tumor are time consuming and ...
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Face Recognition Using Zernike Moments, SIFT and Feed Forward Neural Network
... The main objective of the proposed approach is to generate an algorithm for face recognition that recognizes face with high accuracy. Also it aims to provide face recognition with variance in pose, scale, translation and ...
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An Unsupervised Learning Method for an Attacker Agent in Robot Soccer Competitions Based on the Kohonen Neural Network
... as feed-forward networks because of their ability in modelling nonlinear phenomenon [8-10], and Reinforcement Learning with its online learning attitude [11,12] frequently have been used by teams competing ...
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Comparison of artificial neural network and multivariate regression methods in prediction of soil cation exchange capacity (Case study: Ziaran region)
... neural network PTF with eight hidden neurons was able to predict CEC better than the regression ...that network models are in general more suitable for capturing the non-linearity of the relationship ...
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