Artificial Neural Networks: Methods and Applications
As an extension of artificial intelligence research, artificial neural networks (ANN) aim to simulate intelligent behavior by mimicking the way that biological neural networks function. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to c...
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Weitere Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Totowa, NJ
Humana Press
2009
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Schriftenreihe: | Methods in Molecular Biology™
458 |
Schlagworte: | |
Online-Zugang: | UBR01 TUM01 Volltext |
Zusammenfassung: | As an extension of artificial intelligence research, artificial neural networks (ANN) aim to simulate intelligent behavior by mimicking the way that biological neural networks function. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. In the tradition of the highly successful Methods in Molecular Biology™ series, this volume exhibits clear, easy-to-use information with many step-by-step laboratory protocols. Comprehensive and state-of-the-art, Artificial Neural Networks is an excellent guide to this accelerating technological field of study |
Beschreibung: | 1 Online-Ressource (X, 254 p. 74 illus) |
ISBN: | 9781603271011 |
DOI: | 10.1007/978-1-60327-101-1 |
Internformat
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spelling | Artificial Neural Networks Methods and Applications edited by David J. Livingstone Totowa, NJ Humana Press 2009 1 Online-Ressource (X, 254 p. 74 illus) txt rdacontent c rdamedia cr rdacarrier Methods in Molecular Biology™ 458 As an extension of artificial intelligence research, artificial neural networks (ANN) aim to simulate intelligent behavior by mimicking the way that biological neural networks function. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. In the tradition of the highly successful Methods in Molecular Biology™ series, this volume exhibits clear, easy-to-use information with many step-by-step laboratory protocols. Comprehensive and state-of-the-art, Artificial Neural Networks is an excellent guide to this accelerating technological field of study Computer Science Artificial Intelligence (incl. Robotics) Neurosciences Computer Science, general Computer science Artificial intelligence Livingstone, David J. edt Erscheint auch als Druck-Ausgabe 9781588297181 https://doi.org/10.1007/978-1-60327-101-1 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Artificial Neural Networks Methods and Applications Computer Science Artificial Intelligence (incl. Robotics) Neurosciences Computer Science, general Computer science Artificial intelligence |
title | Artificial Neural Networks Methods and Applications |
title_auth | Artificial Neural Networks Methods and Applications |
title_exact_search | Artificial Neural Networks Methods and Applications |
title_full | Artificial Neural Networks Methods and Applications edited by David J. Livingstone |
title_fullStr | Artificial Neural Networks Methods and Applications edited by David J. Livingstone |
title_full_unstemmed | Artificial Neural Networks Methods and Applications edited by David J. Livingstone |
title_short | Artificial Neural Networks |
title_sort | artificial neural networks methods and applications |
title_sub | Methods and Applications |
topic | Computer Science Artificial Intelligence (incl. Robotics) Neurosciences Computer Science, general Computer science Artificial intelligence |
topic_facet | Computer Science Artificial Intelligence (incl. Robotics) Neurosciences Computer Science, general Computer science Artificial intelligence |
url | https://doi.org/10.1007/978-1-60327-101-1 |
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