Key points are not available for this paper at this time.
Telephone traffic of busy hour is one of indicators of load capacity of telecommunication network, which has a significant meaning to dilate and modify the network. A good performance of predicting the monthly busy hour traffic load is cared about by the mobile operators. As a promising learning theory, support vector machine (SVM) has been studied and applied in a wide area, such as financial markets and weather forecast. In this paper, we use SVM to forecast monthly busy hour traffic load of two regions in Xinjiang. A good result has been achieved via an improved grid search method for the search of hyper-parameter of SVM.
Han et al. (Thu,) studied this question.