Parallel and optimized genetic Elman network for <sup>252</sup>Cf source-driven verification system

Peng FENG; Biao WEI; Jing JIN

doi:10.13538/j.1001-8042/nst.26.040404

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Parallel and optimized genetic Elman network for ²⁵²Cf source-driven verification system

NUCLEAR ELECTRONICS AND INSTRUMENTATION | Updated：2021-01-20

- Parallel and optimized genetic Elman network for ²⁵²Cf source-driven verification system
- Nuclear Science and Techniques Vol. 26, Issue 4, Article number: 040404(2015)
- Affiliations：
  
  1.Key Laboratory of Opto-electronics Technology & System, Ministry of Education, Chongqing University, Chongqing 400044, China
- Author bio：
  
  Corresponding author, coe-fp@cqu.edu.cn
- Funds：
- DOI：10.13538/j.1001-8042/nst.26.040404
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Peng FENG, Biao WEI, Jing JIN. Parallel and optimized genetic Elman network for ²⁵²Cf source-driven verification system. [J]. Nuclear Science and Techniques 26(4):040404(2015)
DOI：

Peng FENG, Biao WEI, Jing JIN. Parallel and optimized genetic Elman network for ²⁵²Cf source-driven verification system. [J]. Nuclear Science and Techniques 26(4):040404(2015) DOI： 10.13538/j.1001-8042/nst.26.040404.

摘要

Abstract

The ,252,Cf source-driven verification system (SDVS) can recognize the enrichment of fissile material with the enrichment-sensitive autocorrelation functions of a detector signal in ,252,Cf source-driven noise-analysis (SDNA) measurements. We propose a parallel and optimized genetic Elman network (POGEN) to identify the enrichment of ,235,U based on the physical properties of the measured autocorrelation functions. Theoretical analysis and experimental results indicate that, for 4 different enrichment fissile materials, due to higher information utilization, more efficient network architecture, and optimized parameters, the POGEN-based algorithm can obtain identification results with higher recognition accuracy, compared to the integrated autocorrelation function (IAF) method.

关键词

Keywords

Nuclear noise analysisNeutron detectionParallel and optimized genetic Elman networkEnrichment identification

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Parallel and optimized genetic Elman network for 252Cf source-driven verification system

DOI：10.13538/j.1001-8042/nst.26.040404

摘要

Abstract

关键词

Keywords

references

Parallel and optimized genetic Elman network for ²⁵²Cf source-driven verification system