Abstract
In the early days of artificial intelligence (AI), artificial neural networks (ANNs) were considered a promising approach to find good learning algorithms to solve practical application problems [189]. Perhaps, a certain unjustified hype was associated to their use, since, nowadays, ANNs seem to have less appeal for researchers. In fact, they are not considered to be among the top 10 data mining techniques [237]. Moreover, publications using ANNs are found not to be backed by a sound statistical analysis [75] and that statistical evaluation of ANNs experiments is a necessity [74]. There are, however, applications in which ANNs have been successfully used. Among such applications, there are the applications in the agricultural-related areas which are discussed in Section 5.4 of this chapter. Therefore, even though they may not be so appealing for some researchers anymore, we decided to dedicate this chapter to ANNs.
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© 2009 Springer Science+Business Media, LLC
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Mucherino, A., Papajorgji, P.J., Pardalos, P.M. (2009). Artificial Neural Networks. In: Data Mining in Agriculture. Springer Optimization and Its Applications, vol 34. Springer, New York, NY. https://doi.org/10.1007/978-0-387-88615-2_5
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DOI: https://doi.org/10.1007/978-0-387-88615-2_5
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Publisher Name: Springer, New York, NY
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Online ISBN: 978-0-387-88615-2
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