Please use this identifier to cite or link to this item:
|Title||Forecasts of Female Breast Cancer Referrals Using Grey Prediction Model GM(1,1)|
Breast Cancer forecasting is an important matter for governments, health sector investors, and other related companies. Although there are different forecasting models, choosing the suitable model is of great significance. This paper focuses on utilizing the performance of grey prediction model GM (1, 1) to the monthly total number of women referrals for Breast Cancer in Gaza Strip\Palestine from January 2002 to December 2016. The results show that the GM (1, 1) model exhibits good forecasting ability according to the MAPE criteria. Moreover, the forecasting results are compared with the results of exponential smoothing state space (ETS) and ARIMA models. The three techniques do similarly well in forecasting process. However, GM (1, 1) outperforms the ETS and ARIMA techniques according to forecasting error accuracy measure MAPE.
|Published in||Applied Mathematical Sciences|
|Series||Volume: 11, Number: 54|
|Item link||Item Link|
|Files in this item|