multi-layer perceptron networks (MLPNs)
Combining gene expression programming and genetic algorithm as a powerful hybrid modeling approach for pear rootstocks tissue culture media formulation
... Background: Predicting impact of plant tissue culture media components on explant proliferation is important especially in commercial scale for optimizing efficient culture media. Previous studies have focused on ...
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Evaluation of 1 D tracer concentration profile in a small river by means of Multi Layer Perceptron Neural Networks
... separate networks are used: N1 concerns the profile’s rising limb ...of networks N1 – N4; version V2 consisted of networks N1 – ...neural networks are summarized in Table ...
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A Survey on Applications of Multi Layer Perceptron Neural Networks in DOA Estimation for Smart Antennas
... wireless networks and therefore, it is one of the most significant areas of study in wireless communications ...establishing networks optimize quality of service and support operational transparency in the ...
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Electrochemical Discharge Machining – An Overview
... a Multi-layer perceptron neural network (multi-layer PNN) model to infer the real-time and fine- grained transportation carbon emission in each region, based on heterogeneous ...
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Advanced approach to numerical forecasting using artificial neural networks
... neural networks can be used for forecasting and they are able to work with extremely big data sets in reasonable ...with Multi Layer Perceptron network with Back-propagation learning algorithm ...
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Identification and Prediction of Internet Traffic Using Artificial Neural Networks
... In this paper we present an artificial neural network (ANN) model based on the multi-layer perceptron (MLP) for analyzing internet traffic over IP networks. We used the input and output data ...
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Parkinson’s Disease Detection Using Biogeography-Based Optimization
... the Multi-layer Perceptron Neural Network (MLP) and Biogeography-based Optimization ...Backpropagation Multi-layer Perceptron Neural Networks, Radial Basis Functions ...
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A Hybrid Method for Compression of Solar Radiation Data Using Neural Networks
... Neural Networks (ANN), namely Multi-layer perceptron neural network (MLPNN), Cascade feed forward back propagation (CFNN) and Elman back propagation ...
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Data Aggregation Framework for Clustered Sensor Networks Using Multi Layer Perceptron Neural Network
... Sensor network consists of many nodes and they are deployed closely. The positions of the nodes are not pre planned. These sensor nodes are helpful for disaster relief operations. There are many different types of ...
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Intrusion Detection System using SMIFS and Multi class Multi layer Perceptron
... Neural Networks (ANN) is computing systems inspired from the biological neural networks of human and animal ...neural networks are constructed to classify the ...
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Open Source Software Survivability Prediction Using Multi Layer Perceptron
... Each layer in a neural network is made up of several such perceptrons, which take in some input, apply an activation function on the input and output some value based on the ...neural networks using ...
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Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning
... one layer perceptron (delta rule), it is based on minimizing the difference between the desired output and the real output, through descent error gradient method ...input layer. The network then ...
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Comparison between Multi Layer Perceptron and Radial Basis Function Networks for Sediment Load Estimation in a Tropical Watershed
... Multi-Layer Perceptron (MLP) is a popular architecture used in ...input layer, the neurons in this first layer propagate the weighted data and randomly selected bias through the hidden ...
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Seismic Signal Classification using Multi Layer Perceptron Neural Network
... Seismic waves can be produced by many types of sources. The latter include tectonic, quarry blast, underground nuclear explosions and cultural activities. These seismic waves are detected by seismic monitoring ...
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A GENETIC ALGORITHM OPTIMIZED MULTI-LAYER PERCEPTRON FOR SOFTWARE DEFECT PREDICTION
... Most broadly utilized neural network model for classification is MLP in light of one or all the more consecutively joined layers of perceptron. MLP model considered in this paper fits in with the feed forward ...
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Estimation of soil parameters over bare agriculture areas from C band polarimetric SAR data using neural networks
... on multi-layer perceptron (MLP) neural networks was ...neural networks were trained and validated on a noisy simulated dataset generated from the Integral Equation Model (IEM) on a wide ...
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KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING
... Neural Networks is to extract rules that can be provided to the ...from Multi-layer Perceptron model trained by Back Propagation algorithm) is integrated with a Neural Network for fast and ...
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Multi criteria validation of artificial neural network rainfall runoff modeling
... comprehensive multi- criteria validation test for rainfall-runoff modeling by artifi- cial neural ...the multi layer perceptron with 4 hidden layers (MLP4) is the best ANN for the basin ...
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Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer
... The architecture of the MLP corresponds to the dataset. The size of input and output layers and the number of dataset attributes are static according to the dataset. While the size of hidden layer is dynamic. The ...
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A Comparative Study of Nonlinear Time Varying Process Modeling Techniques: Application to Chemical Reactor
... neural networks and the second is a Multi Layer Perceptron ...input layer, an output layer and usually one or more hidden ...
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