multilayer perceptron neural networks
Characterization of Lossy SIW Resonators Based on Multilayer Perceptron Neural Networks on Graphics Processing Unit
... of Multilayer Perceptron Neural Networks (MLPNN) on GPU, has been ...Artificial Neural Networks (ANNs) have been recognized as useful alternative to conventional approaches ...
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System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
... Abstract. Recently, some researchers have focused on the applications of neural networks for system identification. In this paper, a Hammerstein model of a quarter car passive suspension system is ...
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Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer
... artificial neural networks are applied to find solutions to many problems because of their computational ...multi-layer perceptron (MLP) is widely ...
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Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads
... as neural network has led to novel solutions for this ...of neural networks – multilayer perceptron and radial basis function – were developed for predicting equivalent continuous sound ...
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Reducing Error Signal in Multilayer Perceptron Neural Networks using MLP for Label Ranking
... true perceptron performs binary classification, a neuron in a multilayer perceptron is free to either perform classification or regression, depending upon its activation ..."multilayer ...
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Evaluating the effect of salinity on corn grain yield using multilayer perceptron neural networks
... MS where the degree of dissimilarity coefficient between MCW and MLR was 1.1563, Connection Weights (CW), Partial Derivatives (PD), (Gervey et al., 2003), and Profile Method (PM) showed moderate performance ...
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DISCRETE WAVELET TRANSFORM AND S-TRANSFORM BASED TIME SERIES DATA MINING USING MULTILAYER PERCEPTRON NEURAL NETWORK
... Other features like mean, skewness, and factors can provide distinction between patterns. In a practical situation the time series data collected from the power network could run into several gigabytes and in such a case ...
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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 watershed ...
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An Algorithm For Training Multilayer Perceptron (MLP) For Image Reconstruction Using Neural Network Without Overfitting.
... MLP networks are typically used in supervised learning ...them. Multilayer Perceptron (MLP) network is a popular learning algorithm in a sense that neural network knows the desired output and ...
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Multilayer Perceptron Neural Analysis of Edge Coupled and Conductor-Backed Edge Coupled Coplanar Waveguides
... Artificial Neural Networks (ANNs) have been introduced for microwave modeling, simulation and ...Multi-Layer Perceptron Neural Networks (MLPNNs). The results of neural models ...
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Short-term prediction of NO2 and NOx concentrations using multilayer perceptron neural network: a case study of Tabriz, Iran
... cial neural networks, support vector machines) regres- sion models are now available, which have the ability to relate the input and output variables (Singh et ...
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A Novel Biometric Authentication System using Keystroke Dynamics and Optimized Multilayer Perceptron Neural Network
... dynamics, multilayer perceptron neural network and most valuable player ...artificial neural networks is the network ...the neural network and unknown set of network parameters ...
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A hybrid BP and HSA for enhancing a multilayer perceptron learning
... Artificial Neural Networks (ANNs) also known as Neural Networks are computational models based on the human brain microstructure which consists of billions of neurons which act as ...
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Self-organizing map and multilayer perceptron for malay speech recognition
... Zbancioc and Costin, 2003) and connectionist approaches (Watrous, 1988; Hochberg et al., 1994). Instead of Hidden Markov Model (HMM), the use of neural networks has become another idea in speech recognition ...
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Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment
... Second, but not least, the nature of subjective analysis of speech signals is highly fuzzy. As a result, a fuzzy sys- tem should be appropriate to solve this problem. However, the equivalence between feedforward ...
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A Prediction Model for Population Dynamics of Cotton Pest (Thrips tabaci Linde) using Multilayer Perceptron Neural Network
... [16]. Neural Networks (NN) is one of the most powerful AI techniques that are capable of learning from a set of data ...[17]. Neural network modeling has been extensively recognized as a dominant ...
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On the Performance of Multilayer Perceptron in Profiling Side-channel Analysis
... the neural network family: multilayer perceptron and convolutional neural ...Convolutional neural net- works are often favored as results suggest better performance, especially in ...
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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 neural network technique has gained the most attention as an accurate, fast method yielding results somewhat superior to the conventional methods due mainly to the independence from any prior knowledge about ...
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Heart Disease Prediction System Using Multilayer Perceptron
... artificial neural network, naive bayes are used to discover knowledge in database and for medical research, particularly in Heart disease ...models Neural Networks predicts heart disease with highest ...
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The Use of Group Method of Data Handling and Multilayer Perceptron Neural Network for the Prediction of Significant Wave Height
... of neural networks (NNs) and auto-regressive models, the authors in [3] reported NN models to be more ...feed-forward neural network (FFNN) to obtain significant wave heights and average wave periods ...
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