A low-order functional observer is designed to estimate the scheduling parameters required for LPV controller.
A clustering technique based on an interpretation of belief functions combined to the least squares algorithm is used to estimate the scheduled parameters.
We used a proportional hazard model to estimate the mortality schedule of an individual having relative risk R at a specific age x.
Ship lines are on a first-come/first serve booking system and estimate the ship sail schedule and delivery.
Discrete event simulation (DES) [70] was the main simulation technique to estimate the performance of scheduling heuristics [46, 51, 95].
We considered the intent-to-treat efficacy as the weighted average of the efficacy for full schedule and the efficacy for partial schedule and used that to estimate the effectiveness of a partial schedule.
Late work objective functions estimate the quality of a schedule based on durations of late parts of activities, not taking into account the amount of delay for fully late activities.
Month 2 data from the 0,1-month schedule was used to estimate the AUC for the 0,1,7-month schedule.
A stochastic-approximation-based algorithm is also provided to estimate the key parameters of the scheduling scheme online.
Following selection of facilities, ART clinic appointment and attendance registers were used to estimate the total number of patients scheduled to attend the ART clinic and to select a random position in the queue of patients on the day of data collection.
