COMPUTATIONAL INTELLIGENCE AS A TOOL FOR SMALL MODULAR REACTORS

被引：0

作者：

Manic, Milos ^{[1
]}

Sabharwall, Piyush ^{[1
]}

机构：

[1] Univ Idaho, Idaho Falls, ID USA

来源：

PROCEEDINGS OF THE ASME SMALL MODULAR REACTORS SYMPOSIUM (SMR 2011) | 2012年

关键词：

HEAT-EXCHANGER; NEURAL-NETWORKS; PERFORMANCE; PREDICTION; SIMULATION;

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Computational intelligence techniques (CITs) traditionally consist of artificial neural networks (ANNs), fuzzy systems and genetic algorithms. This article overviews diverse implementations of ANNs, which are the most prominent in nuclear engineering problems, especially for small modular reactors (SMRs). Advanced computational intelligence-based tools will allow data to be transformation into knowledge, thus improving understanding, predictability (can be seen from the two case studies for thermal-hydraulic prediction), sustainability, and performance of SMRs with real time analysis and monitoring.

引用

页码：299 / 310

页数：12

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