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Artificial Neural Networks: History and State of the Art
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Author(s): Paulo Botelho Pires (CEOS.PP, ISCAP, Polytechnic Institute of Porto, Portugal), José Duarte Santos (Accouting and Business School, Polytechnic of Porto, Portugal)and Inês Veiga Pereira (Accounting and Business School, Polytechnic of Porto, Portugal)
Copyright: 2025
Pages: 25
Source title:
Encyclopedia of Information Science and Technology, Sixth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Founding Editor-in-Chief, Information Resources Management Journal (IRMJ), USA)
DOI: 10.4018/978-1-6684-7366-5.ch037
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Abstract
This chapter contains a description of the historical evolution of artificial neural networks since their inception, with the appearance of the first relevant learning method by Paul Werbos in 1986, which remained ignored until it was discovered simultaneously by three groups of independent researchers: LeCun (1986); Parker (1985); and Rumelhart, Hinton, and Williams (1986). The basic concepts and definitions are also described, followed by the different typologies and the most relevant learning algorithms, most notably the backpropagation algorithm. The most recent advances in artificial neural networks are also described, highlighting convolutional neural networks and deep learning.
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