The hybrid Huberized support vector machine (HHSVM) with the elastic-net penalty has been developed for cancer tumor classification based on thousands of gene expression measurements. In this paper, we develop a Bayesian formulation of the hybrid Huberized support vector machine for binary classification. For the coefficients of linear classification boundary, we propose a new type of prior, wh...

Energy consumption time series consists of complex linear and non-linear patterns and are difficult to forecast. Neither autoregressive integrated moving average (ARIMA) nor artificial neural networks (ANNs) can be adequate in modeling and predicting energy consumption. The ARIMA model cannot deal with nonlinear relationships while the neural network model alone is not able to handle both linea...

This paper proposes a hybrid multi-step-ahead forecasting model based on two stages to improve monthly pelagic fish-catch time-series modeling. In the first stage, the stationary wavelet transform is used to separate the raw time series into a high frequency (HF) component and a low frequency (LF) component, whereas the periodicities of each time series is obtained by using the Fourier power sp...

This paper proposes a hybrid multi-step-ahead forecasting model based on two stages to improve pelagic fish-catch time-series modeling. In the first stage, the Fourier power spectrum is used to analyze variations within a time series at multiple periodicities, while the stationary wavelet transform is used to extract a high frequency (HF) component of annual periodicity and a low frequency (LF)...

The main objective of transfer learning is to reuse knowledge acquired in a previous learned task, in order to enhance the learning procedure in a new and more complex task. Transfer learning comprises a suitable solution for speeding up the learning procedure in Reinforcement Learning tasks. In this work, we propose a novel method for transferring models to a hybrid reinforcement learning agen...

data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

Many authors have examined lot sizing, scheduling and sequence of multi-product flow shops, but most of them have assumed that set up times are independent of sequence. Whereas dependence of set up times to sequence is more common in practice. Hence, in this paper, we examine the discussed problem with hypothesis of dependence of set up times to sequence and cyclic schedule policy in basic peri...