Application of Extreme Learning Machines to inverse neutron kinetics
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- 作者：Paolo Picca ppicca@email.arizona.edu" class="auth_mail" title="E-mail the corresponding author ; Roberto Furfaro ; robertof@email.arizona.edu" class="auth_mail" title="E-mail the corresponding author
- 关键词：Inverse neutron kinetics ; Accelerator-driven system ; Artificial Neural Network ; Extreme Learning Machines
- 刊名：Annals of Nuclear Energy
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：100
- 期：part_P2
- 页码：1-8
- 全文大小：909 K
文摘
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The paper applies the Extreme Learning Machines (ELMs) to inverse reactor problems.
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Multi-group transport model is used for the inversion as opposed to point kinetics.
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ELMs are compared against Artificial Neural Networks (ANNs).
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Various options are tested to improve the reliability of the estimation.
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Results highlight the potential of the ELM approach.