EMS Short Term Demand Forecast
Date Issued
2015
Date
2015
Author(s)
Su, Chen-Hsi
Abstract
The pre-hospital Emergency Medical Service (EMS) provides the professional treatment and the transport of patients. To provide an efficiency pre-hospital EMS, we conduct the demand forecasting spatially and temporally. We have chosen to use Artificial Neural Network (ANN), Poisson Regression and Fast Fourier Transform (FFT) to train the forecasting model and predict the demand in different spatial and time units. In this work, Geographic Information System (GIS) is utilized to analyze the distribution of forecasting demand and to discretize the study area into different spatial scales. The prediction model could serve as a reference for future response operations.
Subjects
Emergency Medical Service
Geographic Information System
Demand Forecast
Artificial Neural Network
Poisson Regression
Fast Fourier Transform
Type
thesis
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