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Artificial neural networks in environmental sciences and chemical engineering

Title
Artificial neural networks in environmental sciences and chemical engineering
Type
Chapter or Part of a Book
Year
2011
Authors
Martins, FG
(Author)
FEUP
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Goncalves, DJD
(Author)
Other
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J. Peres
(Author)
FEUP
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Book
Pages: 55-74
ISBN: 9781613242858
Indexing
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-008-YRX
Abstract (EN): Artificial neural networks have been used for a long time in a wide range of fields inside Environmental Sciences and Chemical Engineering. The main reason for this extensive utilization is the ability of this technique to model easily the complexity of the systems related with these fields, keeping most of the valuable original information about each system. The feedforward artificial neural networks are the most commonly used topology due to the inherent simple architecture, the diversity of the available training algorithms, and the good performances. Besides feedforward artificial neural networks, the self organizing maps, or also called Kohonen neural networks, have as well relevant applications. In Environmental Sciences, the most relevant applications appear in modelling for both environmental and biological processes. In Chemical Engineering, artificial neural networks have been applied mainly in: i) modelling; ii) control; and iii) development of software sensors. This chapter compiles several applications that have been published recently concerning the subjects referred above. A special attention is given to the relevance of the cases, the procedures/techniques, and the ability to be extrapolated to other applications.
Language: English
Type (Professor's evaluation): Scientific
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