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Neuro-Fuzzy Applications in Dialysis Systems

  • Chapter
Modeling and Control of Dialysis Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 405))

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.

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Authors and Affiliations

  1. Computer and Software Engineering Department, Faculty of Engineering, Misr University for Science & Technology (MUST), 6th of October City, Egypt

    Ahmad Taher Azar

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  1. Ahmad Taher Azar
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Correspondence to Ahmad Taher Azar .

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  1. Faculty of Engineering,, Misr University for Science &, Computer and Software Engineering Depart, Al-Motamayez District, 6th of October City, 12566, Egypt

    Ahmad Taher Azar

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Azar, A.T. (2013). Neuro-Fuzzy Applications in Dialysis Systems. In: Azar, A. (eds) Modeling and Control of Dialysis Systems. Studies in Computational Intelligence, vol 405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27558-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-27558-6_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27557-9

  • Online ISBN: 978-3-642-27558-6

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