Artificial Neural Networks

Antonio Mucherino (), Petraq J. Papajorgji () and Panos M. Pardalos ()
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Antonio Mucherino: University of Florida
Petraq J. Papajorgji: University of Florida
Panos M. Pardalos: University of Florida

Chapter Chapter 5 in Data Mining in Agriculture, 2009, pp 107-122 from Springer

Abstract: 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.

Keywords: Neural Network; Hide Layer; Output Layer; Input Layer; Hide Neuron (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/978-0-387-88615-2_5

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