In this research, a hybrid wavelet-artificial neural network (WANN) and a geostatistical method were proposed for spatiotemporal prediction of the groundwater level (GWL) for one month ahead. For this purpose, monthly observed time series of GWL were collected from September 2005 to April 2014 in 10 piezometers around Mashhad City in the Northeast of Iran. In temporal forecasting, an artificial...

Lot output time prediction is a critical task to a wafer fabrication plant (wafer fab). To enhance the effectiveness, a look-ahead FBPN incorporating the future release plan is constructed in this study. Three nearest exponentially discounted future workloads, modified from Chen’s nearest future discounted workloads, are proposed for the look-ahead function. According to experimental results, t...

The present paper is focused on short-term prediction of air-conditioning (AC) load of residential buildings using the data obtained from a conventional smart meter. The AC load, at each time step, is separated from smart meter’s aggregate consumption through energy disaggregation methodology. The obtained air-conditioning load and the corresponding historical weather data are then employed as ...

This paper focuses on different methods of estimation and forecasting in first-order integer-valued autoregressive processes with Poisson-Lindley (PLINAR(1)) marginal distribution. For this purpose, the parameters of the model are estimated using Whittle, maximum empirical likelihood and sieve bootstrap methods. Moreover, Bayesian and sieve bootstrap forecasting methods are proposed and predict...

In this paper, we propose a Fused Two-Level (FTL) branch predictor combined with an Ahead Calculation method. The FTL predictor is derived from the fusion hybrid predictor. It achieves high accuracy by adopting PAp-base Geometrical History Length (p-GEHL) prediction, which is an effective prediction scheme exploiting local histories. The p-GEHL predictor has several prediction tables indexed fr...

Multimedia services became a major part of the internet network traffic. The bursty characteristics of the video traffic, produced by applications like video on demand, video broadcasting or videoconferencing, make it difficult to fulfill the Quality of Service (QoS) of the multimedia applications. Therefore it is important to utilize congestion control procedures. One of the procedures used to...

The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead pr...

Predicting traffic generated by multimedia sources is needed for effective dynamic bandwidth allocation and for multimedia quality-of-service (QoS) control strategies implemented at the network edges. The time-series representing frame or visual object plane (VOP) sizes of an MPEG-coded stream is extremely noisy, and it has very long-range time dependencies. This paper provides an approach for ...