distributed and that this is completely specified. It is also shown that the coefficient of variation is unaffected by the size …

Forecasting category or industry sales is a vital component of a company’s planning and control activities. Sales for … varying model significantly outperformed previous models both in terms of fitting and forecasting the sales data. …

Numerous econometric models have been proposed for forecasting property market performance, but limited success has …

in stock forecasting. Neural networks are viewed as one of the more suitable techniques. In this study, an experiment on … the forecasting of the Stock Exchange of Thailand (SET) was conducted by using feedforward backpropagation neural networks … neural network models in the forecasting of SET. Several global and local factors influencing the Thai stock market were used …

forecasting methods employ cumulative production volume instead of time as the crucial explanatory variable, following Wright … work goes beyond identifying the most relevant factors in cost innovation. Our goal is to provide practical forecasting … information technology, Technological Forecasting & Social Change, 73 (2006) 1061-1083. H. Koh, C.L. Magee, A functional approach …

) power flows. The first method involving neural network load forecasting and simultaneous equations can only be applied to … Queensland electricity network with an error of approximately 5%. The second method of forecasting the cutset flows directly from … 10% MAE. Results indicate that the cutset flow forecasting tool is accurate, robust and adaptable to suit the …

was therefore set up as a simultaneous estimation and forecasting effort which permitted to integrate various, usually …