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multilayer perceptron neural network

A Novel Biometric Authentication System using Keystroke Dynamics and Optimized Multilayer Perceptron Neural Network

A Novel Biometric Authentication System using Keystroke Dynamics and Optimized Multilayer Perceptron Neural Network

... artificial neural network (ANN) is employed to verify the user via their typing rhythm of the ...natural neural system [10]. The multilayer perceptron neural network ...

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The Use of Group Method of Data Handling and Multilayer Perceptron Neural Network for the Prediction of Significant Wave Height

The Use of Group Method of Data Handling and Multilayer Perceptron Neural Network for the Prediction of Significant Wave Height

... The prediction of significant wave height is important in the planning, design, and operation of coastal and ocean structures. Although several empirical methods, numerical models, and soft-computing techniques to ...

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Automated epileptic seizures detection using multi-features and multilayer perceptron neural network

Automated epileptic seizures detection using multi-features and multilayer perceptron neural network

... Detection of epileptic seizure activities from long-term multi-channel electroencephalogram (EEG) signals plays a sig- nificant role in the timely treatment of the patients with epilepsy. Visual identification of ...

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Rainfall runoff modeling by multilayer perceptron neural network for LUI river catchment

Rainfall runoff modeling by multilayer perceptron neural network for LUI river catchment

... of Multilayer Perceptron neural network (MLPNN) for the continuous and event based rainfall-runoff modeling to evaluate its performance for a tropical catchment of Lui River in ...

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DISCRETE WAVELET TRANSFORM AND S-TRANSFORM BASED TIME SERIES DATA MINING USING MULTILAYER PERCEPTRON NEURAL NETWORK

DISCRETE WAVELET TRANSFORM AND S-TRANSFORM BASED TIME SERIES DATA MINING USING MULTILAYER PERCEPTRON NEURAL NETWORK

... Three different wavelet based techniques are outlined here for nonstationary time series that occur in power networks due to various stochastic disturbances. They are denoted as Methods 1 and 2. Each of these described ...

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A Prediction Model for Population Dynamics of Cotton Pest (Thrips tabaci Linde) using Multilayer Perceptron Neural Network

A Prediction Model for Population Dynamics of Cotton Pest (Thrips tabaci Linde) using Multilayer Perceptron Neural Network

... the neural network, standard feed forward Multi-Layer Perceptron (MLP) neural network structure with Backpropagation training ...

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Short-term prediction of NO2 and NOx
               concentrations using multilayer perceptron neural network: a case study of Tabriz, Iran

Short-term prediction of NO2 and NOx concentrations using multilayer perceptron neural network: a case study of Tabriz, Iran

... Artificial neural networks (ANNs) are able to approxi- mate accurately complicated nonlinear input–output re- lationships. Like their physics-based numerical model counterparts, ANNs require training or ...

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The application of multilayer perceptron neural network in volume of clay estimation: Case study of Shurijeh gas reservoir, Northeastern Iran

The application of multilayer perceptron neural network in volume of clay estimation: Case study of Shurijeh gas reservoir, Northeastern Iran

... the neural network approach ...MLP network could accurately follow the laboratory ...MLP network with the laboratory measured data presented in ...the network to adeptly capture the ...

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An Effective Intelligent Self Construction Multilayer Perceptron Neural Network

An Effective Intelligent Self Construction Multilayer Perceptron Neural Network

... Artificial Neural Networks (ANNs) are one of the most effective, flexible, powerful and attractive techniques used for classification ...as, neural nets, neurocomputers, and parallel distributed processing ...

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An innovative method to forecasting the load with the help of 
		Multilayer Perceptron Neural Network

An innovative method to forecasting the load with the help of Multilayer Perceptron Neural Network

... on neural network which can be significantly split into two distinct ...of neural networks based on artificial intelligence and on the other hand the second approach focuses on the biological ...

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Comparison of daily rainfall forecasting using multilayer perceptron neural network model

Comparison of daily rainfall forecasting using multilayer perceptron neural network model

... Studies by [22-23] examined the forecasting models from different techniques to make a comparison in identifying the best model for prediction of rainfall. The author found out that ANN approach is better than any models ...

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EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network

EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network

... In this paper, we present a sleep-wake classification algo- rithm based on multilayer perceptron (MLP) neural network. It attempts to resolve the intermixing of different sleep stages by ...

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Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment

Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment

... Fourier-lapped multilayer perceptron ...a multilayer perceptron neural network trained by a modified version of the scaled conjugated gradient ...This neural ...

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Evaluating the effect of salinity on corn grain yield using multilayer perceptron neural networks

Evaluating the effect of salinity on corn grain yield using multilayer perceptron neural networks

... Multilayer perceptron neural network (MLP) is a powerful statistical modeling technique in the agricultural ...in multilayer perceptron neural network the current ...

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Vegetation Mapping of a Tomato Crop using Multilayer Perceptron (MLP) Neural Network in Images Acquired by Remote Sensing from a UAV

Vegetation Mapping of a Tomato Crop using Multilayer Perceptron (MLP) Neural Network in Images Acquired by Remote Sensing from a UAV

... Artificial Neural Network (ANN) is a system of interconnected neurons that are used to model non linear ...A Multilayer Perceptron Neural network (MLP) [12] is a class of feed ...

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Seismic Signal Classification using Multi Layer Perceptron Neural Network

Seismic Signal Classification using Multi Layer Perceptron Neural Network

... Artificial neural network [23] involves an arrangement of many simple processing elements, called nodes or neurons, interconnected through weighted connection to implementcomplex non-linear mappings between ...

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APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED

APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED

... artificial neural network (ANN) models, multi layer feed-forward neural network using Levenberg–Marquardt learning algorithm (LMFF) and radial basis function (RBF) models for predicting daily ...

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Multilayer Perceptron Neural Analysis of Edge Coupled and Conductor-Backed Edge Coupled Coplanar Waveguides

Multilayer Perceptron Neural Analysis of Edge Coupled and Conductor-Backed Edge Coupled Coplanar Waveguides

... A neural network consists of many processing elements called neurons, each connected to many ...the network is the matter of altering the connection weights systematically [18] to encode the desired ...

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Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit

Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit

... Artificial Neural Networks (ANNs) is an active field of research, and there exists a large literature on the topic (see [21] and references ...multilayered perceptron neural network (MLPNN), ...

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Short Term Load Forecasting With Perceptron
Artificial Neural Network

Short Term Load Forecasting With Perceptron Artificial Neural Network

... 2.6 Conclusion METHODOLOGY 3.0 Introduction 3.1 Data analysis 3.2 Matlab simulation 3.2.1 Create a multilayer perceptron nntool 3.2.2 Develop input and target data 3.2.3 Trained and simu[r] ...

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