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For non-linear models, differentially of other researches, the goal of this work is the used of only one network for forecast model from the introduction of a new variable that differentiates the type of day, if is weekday or not.
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Therefore, this paper presents an application of the neural network for forecasting the storm surge.
Additionally, most of the researchers employed individual neural network for forecasting.
Therefore, NNM5 selected as the best neural network for forecasting the percentage, velocity and coefficient of water absorption.
This method, called Automated ANNs, is an attempt to develop an automatic procedure for selecting the architecture of an artificial neural network for forecasting purposes.
Hourly meterological data of variables such as temperature, pressure, relative humidity, wind speed, wind direction, sunshine duration and cloudiness from the Germany Weather Station at Stuttgart are used for training and testing the neural network for forecasting solar irradiance.
Accordingly, we constructed a hybrid architecture which comprised an ARIMA model and a neural network for forecasting hepatitis E incidence and validated its efficacy.
A piece of software was created to continuously calculate these parameters in the network, as well as a specially designed Artificial Neural Network, responsible for forecasting the bandwidth occupation.
Therefore, a neural network for probabilistic forecasting is proposed based on the fundamental structure of ANN.
The bagging process reduces estimation errors and variation range of errors compared to using a single neural network for load forecasting.
This paper investigates the effectiveness of the genetic algorithm (GA) evolved neural network for rainfall runoff forecasting and its application to predict the runoff in a catchment located in a semi-arid climate in Morocco.
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