error propagation learning back propagation neural network
Unleashing Power of Artificial Intelligence for Network Intrusion Detection Problem
... Back propagation is a supervised learning method of teaching artificial neural ...of back propagation is to train the net to achieve a balance between the ability to respond ...
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Privacy Preserving Neural Network Learning Using Cloud Computing
... for learning the neural networks and has been widely used in various ...applications. Back propagation method works backward, it calculates the error between output (expected values) ...
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UGC Approved Journal | Archive :: iosrjen
... Back propagation algorithm, the common and most widely used algorithm in training artificial neural network learns by calculating an error between desired and actual output and ...
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Bandwidth Analysis by Introducing Slots in Microstrip Antenna Design Using ANN
... The network has been trained for different coordinate values of both the slots, but in a specified ...the neural network automatically adjusts its weights and threshold values such that the ...
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Application of Artificial Neural Network and Genetic Algorithm for Predicting three Important Parameters in Bakery Industries
... work, neural networks with error back-propagation learning algorithms were applied for predicting three important farinograph properties of dough (water absorption, dough development ...
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Real Time Face Recognition Using Step Error Tolerance BPN
... tasks, neural networks have also been applied in face ...Step Error Tolerance Back-propagation Neural Network ...reducing error in each step of learning which make ...
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Hybrid Prediction Models For Stock Market
... the network what type of behavior is ...an error signal is produced. In each step of iterative process, the error signal activates a control mechanism which applies a sequence of corrective ...
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ECG Signal Compression using Improvised Error Back Propagation Neural Network with GDAL
... improvised Error Back Propagation Neural Network with Gradient Descent Learning rate for network to learn with in an adaptive ...square Error (PRD) between 2 to 7 ...
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Diagnosis of Chronic Kidney Disease Using Machine Learning Algorithms
... Back propagation algorithm is a learning rule for multi-layered Neural ...Networks. Back Propagation networks are fully connected, layered, feed forward networks, in which ...
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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 ...
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A Robust Intrusion Detection System by Utilizing Support Vector Machine and Error Back Propagation Neural Network
... in network security, the challenge is recognize unusual access that could lead to compromising the interconnected ...machine learning techniques such as single classifier and hybrid classifier have the ...
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Bat BP: a new bat based back propagation algorithm for efficient data classification
... Bat is a metaheuristic optimization algorithm developed by Xin-She Yang in 2010 [18]. Bat algorithm is based on the echolocation behavior of microbats with varying pulse rates of emission and loudness. In the proposed ...
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REVIEW PAPER ON AN IMPROVED APPROACH FOR BUSINESS AND MARKET INTELLIGENCE USING ARTIFICIAL NEURAL NETWORK
... We all know the running world is fully depends of computer technique which play vital role in living style as well as working life from here and there. Today’s databases and data repositories contain so much data and ...
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Review Techniques of Data Privacy in Cloud Using Back Propagation Neural Network
... Schlitter introduces horizontal approach for privacy preserving BPN network learning scheme. That enables two or more parties to jointly perform BPN net-work learning without disclosing their ...
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Artificial Neural Network Prediction of Aluminium Metal Matrix Composite with Silicon Carbide Particles Developed Using Stir Casting Method
... artificial neural network technique to predict the mechanical and wear properties of short fiber reinforced polyamide (PA) composites using two experimental databases to train the neural ...
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Comparative Study of different methods used for GPS GDOP Approximation
... the error in the data received by the user[3][4], they are propagation delay, receiver clock offset, satellite position geometry, satellite clock offset ...the error is position calculation is ...
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Sentiment Analysis of Social Media Text Data using Back Propagation in Artificial Neural Networks
... It can be concluded from the mathematical background and subsequent results that the proposed system yields high accuracy for text mining data. The data used here are in the form of tweets. The training algorithm used is ...
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1. Evaluate the performance of power energy output forecasting in photovoltaic cell
... The learning step is an important subject of neural networks; supervised learning and unsupervised learning are two types of learning ...The Back-Propagation (BP) [1] ...
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Research of Teacher’s Performance Evaluation Model Based on AHP and Improved PSO BP Neural Network
... in network training in the same important ...the network structure of improved PSO-BP model is 16-10-1; the particle swarm size of the prediction model is 20; the particle dimension is ...minimum ...
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INVESTIGATING DATA MINING BY ARTIFICIAL NEURAL NETWORK: A CASE OF REAL ESTATE PROPERTY EVALUATION
... The data of the real estate properties used here in this study was arranged in the form of four hundred sets of thirteen element input vector and one element target vector. The attributes that were considered for the ...
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