Keywords: Demand forecasting Genetic algorithm–simulated annealing (GA–SA) Support vector regression (SVR) Autoregressive integrated moving average (ARIMA) General regression neural networks (GRNN) Third generation (3G) mobile phone a b s t r a c t Taiwan is one of the countries with higher mobile phone penetration rate in the world, along with the increasing maturity of 3G relevant products, t...

The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...

The authors have been developing several models based on artificial neural networks, linear regression models, BoxJenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels” of one region. Several comparisons between the different type models have been experimented as well as the features used at the e...

In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficient ...

Spectral analysis of the time series for average annual values globally averaged surface temperature anomaly shows presence harmonics lunar nodal cycle with a period 18.6 years,whichcan be used to predict theseries. Three models theseries were considered: autoregression AR(p), combined model – integrated moving ARIMA(p,d,q) and artificial neural network. It is shown that ARIMA(4,1,4) gives best...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

the main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. recently there have been attempts for using artificial neural networks (anns) in optimizationproblems and some types of anns such as hopfield network and boltzm...