Exponential procedures are widely used as forecasting techniques for inventory control and business planning. A number of modifications to the generalized exponential smoothing (Holt–Winters) approach to forecasting univariate time series is presented, which have been adapted into a tool for decision support systems. This methodology unifies the phases of estimation and model selection into jus...

Most of the inventory control models assume that quality defect never happens, which means production process is perfect. However, in real manufacturing processes, the production process starts its operation in the in-control state; but after a period of time, shifts to the out-of-control state because of occurrence of some disturbances. In this paper, in order to approach the model to real man...

Spam has been one of the most difficult problems to be addressed since the invention of Internet. Outbound spam can reflect the information security level of an organization as most spam emails are generated by compromised computers. Understanding the trend of outbound spam can help organizations adopt proactive policies and measures toward a more informed decision on resource allocation in ter...

In applications, statistical models for images are often restricted to what produces reasonable estimates for the data at hand. In many cases, the principles that allow a model to be restricted can be derived theoretically, in the absence of any data and with minimal applied context. We present three theoretical examples. We interpret local smoothing of spatial lattice data as Bayesian estimati...

This study utilized the data on abaca fiber production and used Holt-Winters model to forecast since studied variable is characterized by a fairly strong intensity of seasonality. For construction forecasts, additive multiplicative models were used. The most accurate forecasts selected basis Mean Square Error, Root Absolute Percentage Scaled Error. It was found that method had higher accuracy, ...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

The extent of smoothing applied to cortical thickness maps critically influences sensitivity, anatomical precision and resolution of statistical change detection. Theoretically, it could be optimized by increasing the trade-off between vertex-wise sensitivity and specificity across several levels of smoothing. But to date neither parametric nor nonparametric methods are able to control the erro...