Artificial Neural Networks: Applications in Food Processing

Rauh C, Delgado A, Park J, Kim YJ, Groß F, Diez Robles L (2016)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2016

Publisher: Elsevier Inc.

Edited Volumes: Reference Module in Food Science

DOI: 10.1016/B978-0-08-100596-5.03125-5

Abstract

Artificial neural networks (ANNs) represent a mathematical approach that permits to mimic the learning process occurring in the brain of mammalians. The present article presents a short overview on ANNs. The basic need of the employment of ANNs in up-to-date food management systems, the theoretical background, and design of ANNs are described shortly. Examples of ANNs in food technology applications are also presented. The last section discusses current and future ANN methods in food technology.

Authors with CRIS profile

Antonio Delgado Lehrstuhl für Strömungsmechanik (LSTM) Jinyoung Park Lehrstuhl für Strömungsmechanik (LSTM) You Jin Kim Lehrstuhl für Strömungsmechanik (LSTM) Frauke Groß Lehrstuhl für Strömungsmechanik (LSTM) Lucia Diez Robles Lehrstuhl für Strömungsmechanik (LSTM)

Involved external institutions

Technische Universität Berlin

Germany (DE)

How to cite

APA:

Rauh, C., Delgado, A., Park, J., Kim, Y.J., Groß, F., & Diez Robles, L. (2016). Artificial Neural Networks: Applications in Food Processing. In Reference Module in Food Science. Elsevier Inc..

MLA:

Rauh, Cornelia, et al. "Artificial Neural Networks: Applications in Food Processing." Reference Module in Food Science. Elsevier Inc., 2016.

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