Application of Artificial Neural Network For Path Loss Prediction In Urban Macrocellular Environment

Prediction of the Reactor’s Operational Conditions The biggest challenge of this procedure is to train network 9 which will predict the operational condition of the fluidized

In this paper, genetic algorithm based artificial neural network hybrid prediction model is proposed to foretell surface roughness and tool wear.. A multiple

In addition, a novelty of this study is the use of PSO to not only reach the relevant lags used in the prediction, but also to determine the best neural network architecture

The use of unsupervised artificial neural network techniques like the self-organizing map (SOM) algorithm has proven to be a useful tool in exploratory data analysis and clustering

This example is used to compare the performance of the proposed technique with the Gauss-TD separation algorithm in [18] and the adaptive spline neural network (ASNN)

In this paper, an RBF neural network was used as a classifier in the face and fingerprint recognition system in which the inputs to the neural network are

All artificial neural networks used in this work showed high accuracy to estimate the moisture, however, the neural network based on the basic density and drying days was the

A mulit-layer artificial neural network, with a backpropagation training algorithm and 11 neurons in the input layer, was used.. In this type of network, network inputs are