1. A method comprising: receiving, at a computing device, a plurality of points, each point representing a time value and a network traffic value representative of traffic on a communication network, the network traffic values and the time values represented by the plurality of points decomposable into a trend component, a seasonality component, a burst component, and a random error component; generating, using machine learning or data mining techniques, a trend equation for calculating the trend component, the trend component taking into account a long-term trend of the network traffic values and one or more sharp changes in network traffic, the sharp changes followed by stable periods and caused by predictable bursts or seasonal network traffic patterns but not accounted for in the seasonality component due to a periodicity of the seasonality component and not accounted for in the burst component due to a granularity of the burst component, the sharp changes taken into account in the trend component by a compensation formula applied to the trend component; generating, using machine learning or data mining techniques, a seasonality equation for calculating the seasonality component; generating, using machine learning or data mining techniques, a burst equation for calculating the burst component; generating a random error equation for calculating the random error component; generating a network traffic equation for predicting future network traffic values corresponding to future time values by combining the trend equation, the seasonality equation, the burst equation, and the random error equation; and providing, via the computing device to a network administrator responsible for the communication network: an indication of a current network capacity, an indication of a projected network usage based on the generated network traffic equation, an indication that the communication network is expected to operate above capacity at a future time corresponding to at least one of the future time values based on a difference between the current network capacity and the projected network usage, and a recommendation including an action for the network administrator to take to improve the current network capacity to meet the projected network usage prior to the future time.