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  • 标题:Pathological Worrying and Artificial Neural Networks
  • 本地全文:下载
  • 作者:Carlos Pelta
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2020
  • 卷号:11
  • 期号:1
  • DOI:10.14569/IJACSA.2020.0110106
  • 出版社:Science and Information Society (SAI)
  • 摘要:Worrying is a cognitive process that focuses on potential future negative events, where the outcome is often uncertain. Worries can arise in chains with one worry leading to another, often without solution. This may give rise to an uncontrollable worrying that may be associated with psychiatric disorders such as anxiety and depression. The generation of progressively more negative chains of worries can lead to a catastrophic phenomenon of pathological worrying. In this article we show that catastrophic worrying can be simulated by using a cascade-correlation algorithm for artificial neural networks.
  • 关键词:Pathological worrying; artificial neural networks; cascade-correlation algorithm
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