Estimation of the Demand for the Blood Bank Using Hybrid PCA-ANFIS Method
Seda Hatice GÖKLER Semra BORAN
AbstractBlood is a vital product that is needed by thousands of people every day due to diseases, surgeries or injuries. Blood banks should accurately determine the amount of blood they should have in their stock to meet blood needs. Therefore, having less blood than necessary in hospitals creates important problems such as not meet need for blood and loss of life. On the other hand, storing large amounts of blood causes deteriorating the blood and causes stock out in other hospitals. The aim of this study is to determine the criteria affecting blood demand and to forecast the blood demand by the machine learning algorithm Adaptive Network Based Fuzzy Inference System (ANFIS) method. However, since the number of impact criteria is high, principal component analysis (PCA) method has been used in order to decrease criteria and eliminate the dependencies between the criteria. The developed hybrid method was applied in a regional blood center.