工學院: 土木工程學研究所指導教授: 陳柏華蘇辰昕Su, Chen-HsiChen-HsiSu2017-03-132018-07-092017-03-132018-07-092015http://ntur.lib.ntu.edu.tw//handle/246246/277992緊急醫療需求日漸增加，在資源有限的狀況下，為了及時將病患送達醫院，緊急醫療資源的事先配置極為重要。本研究提供以村里或以網格為空間單位下，應用類神經網路(Artificial Neural Network)、泊瓦松迴歸(Poisson Regression)及快速傅立葉轉換(Fast Fourier Transform)分析需求量之時間序列，用以預測每日、每六小時、每三小時或是每小時EMS需求，同時討論最適之空間單位與時間單位切割方式。本研究以新北市為研究案例，利用地理資訊系統(Geographic Information System)作為離散空間與視覺化預測結果之工具。預測方法和結果可作為未來緊急醫療服務單位的參考。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.2547145 bytesapplication/pdf論文公開時間: 2017/12/1論文使用權限: 同意有償授權(權利金給回饋學校)緊急醫療救護服務(EMS)類神經網路泊瓦松迴歸快速傅立葉轉換需求預測GISEmergency Medical ServiceGeographic Information SystemDemand ForecastArtificial Neural NetworkPoisson RegressionFast Fourier Transformthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/277992/1/ntu-104-R02521526-1.pdf