The Bell System has recently completed studies that are expected to result in substantially improved forecasts for use in network planning. These improved forecasts are achieved through the use of new forecasting algorithms that employ Kalman filter models. To motivate the selection of Kalman filter forecasting procedures, we describe the Bell System's special data characteristics and processing requirements in the network planning process. We also discuss the Kalman filter models, their statistical properties, the model identification process, and certain implementation considerations.
In this paper we investigate the output process of the M/D/1 queuing system. We derive expressions for the distributions and first two moments, in both steady-state and transient conditions, of the following random variables: (1) the time until the nth departure measured from a departure epoch, T0, (2) the time between the n − 1st and nth departures after T0, and (3) the number of departures in (T0, T0 + t]. Further we study the autocorrelation functions of random variables (1) and (2) in the steady state.
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