A Comprehensive Guide to Neural Network Modeling


Steffen Skaar (Editor)

Series: Computer Science, Technology and Applications
BISAC: COM044000

As artificial neural networks have been gaining importance in the field of engineering, this compilation aims to review the scientific literature regarding the use of artificial neural networks for the modelling and optimization of food drying processes.

The applications of artificial neural networks in food engineering are presented, particularly focusing on control, monitoring and modeling of industrial food processes.

The authors emphasize the main achievements of artificial neural network modeling in recent years in the field of quantitative structure–activity relationships and quantitative structure–retention relationships.
In the closing study, artificial intelligence techniques are applied to river water quality data and artificial intelligence models are developed in an effort to contribute to the reduction of the cost of future on-line measurement stations.

Table of Contents

Table of Contents


Chapter 1. Application of Artificial Neural Networks (ANNS) Modelling in Drying Technology of Food Products: A Comprehensive Survey
(Raquel Guiné, Iman Golpour, Maria João Barroca and Mohammad Kaveh, CERNAS-IPV Research Centre, Polytechnic Institute of Viseu, Campus Politécnico, Viseu, Portugal, and others)

Chapter 2. Application of Artificial Neural Networks in the Food Engineering
(Ana Jurinjak Tušek, Davor Valinger, Maja Benković, Jasenka Gajdoš Kljusurić and Tamara Jurina, University of Zagreb, Faculty of Food Technology and Biotechnology, Zagreb, Croatia)

Chapter 3. Artificial Neural Networks as a Chemometric Tool in Analysis of Biologically Active Compounds
(Strahinja Kovačević, Milica Karadžić Banjac, Sanja Podunavac-Kuzmanović and Lidija Jevrić, Faculty of Technology, Department of Applied and Engineering Chemistry, University of Novi Sad, Novi Sad, Serbia)

Chapter 4. River Water Quality Modelling Using Artificial Intelligence Techniques
(Eda Göz, Erdal Karadurmuş and Mehmet Yüceer, Faculty of Engineering, Department of Chemical Engineering, Ankara University, Ankara, Turkey, and others)



“Steffen Skaar’s edited collection A Comprehensive Guide to Neural Network Modeling presents four chapters around various practical applications of artificial neural networks to represent various aspects of the world for awareness, decision-making, research, and other applications. Modeling is representational and strives to offer insights with fidelity to the world, to inform people’s consciousness and actions. This book offers some fresh ideas to the general public about how artificial neural networks (ANNs) can and are being applied in a variety of contexts. If there is one quibble, the title smacks of over-reach in claiming comprehensiveness, given the four chapters from several disciplines. Well beyond, ANNs have been applied in various practical fields, such as finance, medicine, geology, physics, and other areas (Tušek, Valinger, Benković, Kljusurić, & Jurina, 2020, p. 58). This data analytics approach seems very cyborg-ian, combining human insights and machine capabilities…READ MORE– Shalin Hai-Jew for C2C Digital Magazine (Spring/Summer 2021), Instructional Designer/Researcher, Kansas State University

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