Grey system theory can effectively deal with incomplete and uncertain information. The grey model (GM) is the core of grey system theory, which collects available data to obtain the internal regularity without using any assumptions. The forecasting accuracy is related to the sample number n in GM. However, there always exists a time lag just the same as other forecasting methods do although its application can yield exact prediction that is of high repeatability with characteristics depicting high reliability and efficiency. To minimise the lag time for the results of grey prediction (GP), a three-point moving average has been developed and applied on them. Its application to the UK and USA datasets has been proved to be greatly successful and reliable. The mean and maximum errors of the outcomes of GP are tremendously reduced, hence greatly improving the accuracy of prediction. Thus, the combination of grey model GM(1, 1) with three-point moving average has been proved to be a more powerful forecasting tool and yields far much better predictions for vehicle fatality risk rates. (Author/publisher)
Abstract