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Forecasting Emergency Calls with a Poisson Neural Network-based Assemble Model
2019
IEEE Access
Forecasting emergency calls are of great importance in practice. By forecasting the occurrence of unfortunate events, we can learn from these events and further prevent their occurrence in the future. However, because of the uncertainty of event occurrences, it is hard to guarantee their prediction accuracy. In this paper, a combined model, which consists of two parts, is proposed. The first part is a Poisson neural network model (PNN). It is responsible for basic forecasting, and its initial
doi:10.1109/access.2019.2896887
fatcat:uixrdkan7neabdsz2h6edvqgoa