| Title: | Neuro-Fuzzy Applications in Dialysis Systems. In: A.T Azar (ed.), Biofeedback Systems and Soft Computing Techniques of Dialysis, Springer-Verlag GmbH Berlin/Heidelberg, Vol. 405, pp 1223-1274. DOI: 10.1007/978-3-642-27558-6_10. |
| Authors: | Azar AT |
| Year: | 2013 |
| Keywords: | Not Available |
| Journal: | Not Available |
| Volume: | Not Available |
| Issue: | Not Available |
| Pages: | Not Available |
| Publisher: | Not Available |
| Local/International: | International |
| Paper Link: | |
| Full paper | Not Available |
| Supplementary materials | Not Available |
| Abstract: |
Soft computing techniques are known for their efficiency in dealing with complicated problems when conventional analytical methods are infeasible or too expensive, with only sets of operational data available. Its principal constituents are fuzzy logic, Artificial Neural Network (ANN) and evolutional computing, such as genetic algorithm. Neuro-fuzzy controllers constitute a class of hybrid soft computing techniques that use fuzzy logic and artificial neural networks. The advantages of a combination of ANN and Fuzzy Inference system (FIS) are obvious. There are several approaches to integrate ANN and FIS and very often it depends on the application. This chapter gives an overview of a neuro-fuzzy system design with novel applications in dialysis using an adaptive-network-based fuzzy inference system (ANFIS) for the modeling and predicting important variables in hemodialysis process. |
