2018
DOI: 10.48550/arxiv.1806.10873
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Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression

Abstract: Accurately predicting when and where ambulance call-outs occur can reduce response times and ensure the patient receives urgent care sooner. Here we present a novel method for ambulance demand prediction using Gaussian process regression (GPR) in time and geographic space. The method exhibits superior accuracy to MEDIC, a method which has been used in industry. The use of GPR has additional benefits such as the quantification of uncertainty with each prediction, the choice of kernel functions to encode prior k… Show more

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References 23 publications
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