multilayer neural network model
Prediction of gas emission quantity using artificial neural networks
... Artificial Neural Networks (ANN) with known experimental data to predict the gas emission ...Regression Neural Network (GRNN) and Multilayer Feedfoward Neural Network (MLFN) ...
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APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED
... (SVM) model for monthly stream flow prediction and authors recommended to use the PCA and GT techniques for increasing the SVM model performance especially in cases where lack of knowledge about the input ...
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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
... ARMA model for dynamic linear block and a multilayer feed forward neural network to model the static nonlinear[13], least square and SVD for Hammerstein model[11],[8], recursive ...
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Novel Ensemble Neural Network Models for better Prediction using Variable Input Approach
... Artificial Neural Network (ANN) models, namely, Multilayer Perceptron Network (MLPN), Elman Recurrent Neural Network (ERNN), Radial Basis Function Network (RBFN), Hopfield ...
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An artificial neural network model application for the estimation of thermal comfort conditions in mountainous regions, Greece
... used neural network model, the multilayer perceptron (MLP), was used to evaluate the estimated THI values at high altitude based on the air temperature and the relative humidity values at the ...
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The FL-SMIA Network: A Novel Architecture for Time Series Prediction
... FL-SMIA model. This is a novel neural network model that combines the principles of the Functional Link Neural Network (FLNN) with the Self- organizing Multilayer ...
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Evaluation Of Different Software Based Approaches For Deep Packet Inspection
... the multilayer perceptrons neural network can perform position independent matching to solve the ...segment model stated above will be very powerful and will provide high throughput along with ...
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An Effective Intelligent Self Construction Multilayer Perceptron Neural Network
... artificial neural network with extracting most effective features, based on a priori knowledge from a set of training samples, assisted by Apriori algorithm for association rules and particle swarm for ...
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Support Vector Machine to predict the discharge coefficient of Sharp crested w-planform weirs
... using Multilayer Perceptron Neural Network (MLPNN), Radial Basis Neural Network (RBFNN) and support vector machine ...this model is more ...
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Forecasting Malaysia load using a hybrid model
... and multilayer feed-forward neural network are ...hybrid model with selection of the number of hidden nodes for the non linear model are ...
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Prediction Of The Compressive Strength Of Palm Kernel Shell Ash Concrete Using Multilayer Feed Forward Neural Network
... a network can be quantified by the root of the mean squared error (RMSE) difference between the measured and the predicted values, mean absolute error ...the model with the accuracy of a superficial ...
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An Application of ANN Model with Bayesian Regularization Learning Algorithm for Computing the Operating Frequency of C-Shaped Patch Antennas
... artificial neural network (ANN) using bayesian regularization (BR) learning algorithm based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped ...
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FORECAST PERFORMANCE OF UNIVARIATE TIME SERIES AND ARTIFICIAL NEURAL NETWORK MODELS
... FAR model has the capabilities of forecasting Nigerian monthly precipitation better when seasonal and periodic variations are ...on multilayer perception is the most ...SARIMA model when analysing ...
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Gait Recognition Using Deep Learning
... “neural network” was one of the great PR successes of the Twentieth ...“A network of weighted, additive values with nonlinear transfer ...name, neural networks are far from “thinking machines” ...
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Clustering of heterogeneous precipitation fields for the assessment and possible improvement of lumped neural network models for streamflow forecasts
... ral network is proposed for the clustering of precipitation ...rainfall-runoff model for one-day ahead predic- tions is then established based on this ...clustering. Multilayer perceptron ...
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Video Classification with Recurrent Neural Network
... color model is used to extract color features from each ...Recurrent Multilayer Perceptron Neural Network is used to classify videos with the color features model and pattern generated ...
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On the Investigation of Temperature Effects on Oil Relative Permeability: Robust Modeling and Data Assessments
... different epochs/iterations is illustrated. The detailed information of MLP-ANN including the number of hidden and output layer are also listed in Table 2. Particle swarm optimization (PSO) method is utilized in ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... For the set point tracking case, each controller is applied to track the acetone distillate composition at the desired profile. Figures 7, 8 and 9 show the acetone distillate composition using NNMPC, NNDIC and PID ...
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A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
... This paper presents an indirect method for solving a class of FOCPs based on a combination of the Mittag-Leffler function and artificial neural networks. The discussed problem includes the integer and fractional ...
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Economic classification and regression problems and neural networks
... the network performance on new, yet unseen data. Usually if a network is trained, its error on the training set is ...the network starts to behave badly, if the previously unseen vectors are put on ...
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