A Takagi-Sugeno type neuro-fuzzy network for determining child anemia
EXPERT SYSTEMS WITH APPLICATIONS, vol.38, no.6, pp.7415-7418, 2011 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 38 Issue: 6
- Publication Date: 2011
- Doi Number: 10.1016/j.eswa.2010.12.083
- Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.7415-7418
- Kocaeli University Affiliated: Yes
Abstract
Decision-making is a difficult and quite responsible task for doctors. Some of the computer decision models assisted the doctor with some computer decision models. In this study, neuro-fuzzy network has been designed to determine anemia level of a child. The performance analyses have been obtained by leaving-one-out cross-validation. After statistical measurements, it was found that MPE = 0.0018, MAE = 0.2090, MAPE = 0.0511, RMSE = 0.2743 and R-2 = 0.9957 of this developed system. According to these results, the designed neuro-fuzzy network may be considered as adequate close to traditional decision-making methods and thus the designed network can be used effectively for child anemia prediction. (c) 2010 Elsevier Ltd. All rights reserved.