Inventory control systems typically require the frequent updating of forecasts for many different products. In addition to point predictions, interval forecasts are needed to set appropriate levels of safety stock. The series considered in this paper are characterised by high volatility and skewness, which are both time-varying. These features motivate the consideration of forecasting methods t...

Statistical techniques have disadvantages in handling the non-linear pattern. Soft computing (SC) techniques such as artificial neural networks are considered to be better for prediction of data with non-linear patterns. In the real-life, timeseries data comprise complex pattern, and hence it may be difficult to obtain high prediction accuracy rates using the statistical or SC techniques indivi...

Simple exponential smoothing is widely used in forecasting economic time series. This is because it is quick to compute and it generally delivers accurate forecasts. On the other hand, its multivariate version has received little attention due to the complications arising with the estimation. Indeed, standard multivariate maximum likelihood methods are affected by numerical convergence issues a...

This paper has a focus on non-stationary time series formed from small non-negative integer values which may contain many zeros and may be over-dispersed. It describes a study undertaken to compare various suitable adaptations of the simple exponential smoothing method of forecasting on a database of demand series for slow moving car parts. The methods considered include simple exponential smoo...

in many statistical process control applications, the quality of a process is characterized by a profile. a profile is a function in terms of one or more explanatory variables. in profile monitoring, one is interested to monitor the performance of a process or product using this functional relationship. control charts for monitoring nonparametric profiles are useful when the relationship is too...

The article investigates models and methods of electric load forecasting. It is shown that the following power consumption control are currently known: instantaneous norm; at ideal rate; management on forecast value; with use average a moving time interval ("moving window" method). it better to focus those based study estimates, which source information for decisions. main requirements real-tim...

This paper introduces five new univariate exponentially weighted methods for forecasting intraday time series that consist of both intraweek and intraday seasonal cycles. Applications of relevance include forecasting volumes of call centre arrivals, transportation, e-mail traffic and electricity load. The first method that we develop extends an exponential smoothing formulation that has been us...

Pattern modelling in time-series prediction refers to the process of identifying past relationships and trends in historical data for predicting future values. This paper describes the development of a new pattern matching technique for univariate time-series forecasting. The pattern modelling technique out-performs frequently used statistical methods such as Exponential Smoothing on different ...

Control of wellbore pressure during drilling operations has always been important in the oil industry as this can prevent the possibility of well blowout. The present research employs a combination of automatic process control and statistical process control for the first time for the identification, monitoring, and control of both random and special causes in drilling operations. To this end, ...