Application of Extreme Learning Machines to inverse neutron kinetics

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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

class="label">•: The paper applies the Extreme Learning Machines (ELMs) to inverse reactor problems.
class="label">•: Multi-group transport model is used for the inversion as opposed to point kinetics.
class="label">•: ELMs are compared against Artificial Neural Networks (ANNs).
class="label">•: Various options are tested to improve the reliability of the estimation.
class="label">•: Results highlight the potential of the ELM approach.

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