Adaptive forecasting

The specific form of the systematic component applicable to a given forecast depends on the nature of demand. Companies may develop both static and adaptive forecasting methods for each form. We now describe these static and adaptive forecasting methods. 

In adaptive forecasting, the estimates of level, trend, and seasonality are updated after each demand observation. The main advantage of adaptive forecasting is that estimates incorporate all new data that are observed. We now discuss a basic framework and several methods that can be used for this type of forecast. The framework is provided in the most general setting, when the systematic component of demand data has the mixed form and contains a level, a trend, and a seasonal factor. It can easily be modified for the other two cases, however. The framework can also be specialized for the case in which the systanatic component contains no seasonality or trend. We assume that we have a set of historical data for n periods and that demand is seasonal, with periodicity p. Given quarterly data, wherein the pattern repeats itself every year, we have a periodicity of p = 4. 

The four steps in the adaptive forecasting framework are as follows ... 

We now discuss various adaptive forecasting methods. The method that is most appropriate depends on the characteristic of demand and the composition of the systematic component of demand. In each case, we assume the period under consideration to be t. 

If Tahoe Salt uses an adaptive forecasting method for the sell-through data obtained from its retailers. Winter s model is the best choice, because its demand experiences both a trend and seasonality. 

Fig. 21-4. Number of forecast days of high air pollution potential per 5 years (1960-1964), Source Adapted from Holzworth (2).

Ydstie, B. E., Forecasting and control using adaptive coimectionist networks. Comput. Chem. Eng. 14, 583 (1990). 

Artificial satellites, which are now used for communication, broadcast, weather forecast, etc., are equipped with a variety of semiconductor devices, which are often exposed to the high levels of radiation found in space. Such energetic particles, called cosmic rays, cause the degradation and malfunction of semiconductor devices, which lowers both the mission lifetime and reliability of satellites. Using ion beam irradiation facilities at TIARA, which have been uniquely adapted for simulating the radiation environment of space, we have... 

Comparison of sales of therapeutic monoclonal antibodies (mAbs) in 2002 (in white) and forecast for 2008 (in black) (adapted from Reichert and Pavlou, 2004). 

The book presents a well-defined procedure for adding or subtracting independent variables to the model variable and covers how to apply statistical forecasting methods to the serially correlated data characteristically found in clinical and pharmaceutical settings. The standalone chapters allow you to pick and choose which chapter to read first and hone in on the information that fits your immediate needs. Each example is presented in computer software format. The author uses MiniTab in the book but supplies instructions that are easily adapted for SAS and SPSSX, making the book applicable to individual situations. 

Many dissemination technologies have been included because many are available to a proliferant. There is sufficient open literature describing the pros and cons of various types of dissemination to dictate the consideration of all of them by a proliferant. Although most countries and perpetrators could develop the toxic agents and adapt their standard munitions to carry the agents. It is much more difficult, however, to achieve success in effective dispersion and dissemination. Weather observation and forecasting are essential to increase the probability of effective CW dissemination and reduce the risk of injuring friendly forces. 

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