Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel m...

BACKGROUND Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. METHODS Two hybrid models, one composed of...

Surveys show that the mean absolute percentage error (MAPE) is the most widely used measure of forecast accuracy in businesses and organizations. It is however, biased: When used to select among competing prediction methods it systematically selects those whose predictions are too low. This is not widely discussed and so is not generally known among practitioners. We explain why this happens. W...

This study empirically analyzes model accuracy, and applies grey forecasting to handle non-linear problems, insufficient data resources and forecasting involving small samples, and to construct the co-opetition diffusion model for the Lotka–Volterra (L.V.) system. Furthermore, this study examines historical data comprising revenue trends in the Taiwanese IC assembly industry during the past ten...

Service Oriented Systems (SOSs) based on the SOA paradigm are becoming popular thanks to a widely deployed internetworking infrastructure. They are composed by a possibly large number of heterogeneous third-party subsystems and usually operate in a highly varying execution environment, that makes it challenging to provide applications with Quality of Service (QoS) guarantees. A well-established...

Composites based on high density polyethylene (HDPE), pine flour, and organic clay were made by melt compounding and then injection molding. The influence of clay on crystallization behavior, mechanical properties, water absorption, and thermal stability of HDPE/pine composites were investigated. The HDPE/pine composites containing exfoliated clay were made by a two-step melt compounding proced...

This study presents an integrated algorithm for forecasting oil production based on a Genetic Algorithm (GA) with variable parameters using stochastic procedures, time series and Analysis of Variance (ANOVA). The significance of the proposed algorithm is two fold. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the be...

In this study we develop the hybrid models for forecasting in agricultural production planning. Real data of Thailand’s orchid export and Thailand’s pork product are used to validate candidate models. Autoregressive Integrate Moving Average (ARIMA) is also selected as a benchmarking to compare other developed models. The main concept of building the models is to combine different forecasting te...

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors...

Side weirs are used in open channels to control flood and the flow passing through it. Discharge capacity is one of the crucial hydraulic parameters of side weirs. The aim of this study is to determine the effect of the intended dimensionless parameters on predicting the discharge coefficient of triangular labyrinth side weir. MAPE, RMSE, and R2 statistic indexes have been used to assess the ac...